All upcoming events

Vision and Robotics Seminar

Date:
04
Thursday
January
2018
-
04
Tuesday
December
2018
Lecture / Seminar
Time: 12:15 - 13:30
Title: Processing images using nonlinear transforms
Location: Jacob Ziskind Building
Lecturer: Guy Gilboa
Organizer: Faculty of Mathematics and Computer Science
Abstract: Recent studies of convex functionals and their related nonlinear eigenvalue prob ...Recent studies of convex functionals and their related nonlinear eigenvalue problems show surprising analogies to harmonic analysis based on classical transforms (e.g. Fourier). In this talk the total-variation transform will be introduced along with some theoretical results. Applications related to image decomposition, texture processing and face fusion will be shown. Extensions to graphs and a new interpretation of gradient descent will also be discussed.

Foundations of Computer Science Seminar

Date:
22
Monday
January
2018
Lecture / Seminar
Time: 14:30-16:00
Title: Reproducibility in Randomized Log-space
Location: Jacob Ziskind Building
Lecturer: Ofer Grossman
Organizer: Faculty of Mathematics and Computer Science

Seminar in Geometry and Topology

Date:
23
Tuesday
January
2018
Lecture / Seminar
Time: 16:15-17:45
Title: Quantization of extremal metrics and applications
Location: Jacob Ziskind Building
Lecturer: Carl Tipler
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
25
Thursday
January
2018
-
25
Wednesday
January
2108
Lecture / Seminar
Time: 12:15 - 13:30
Title: TBA
Location: Jacob Ziskind Building
Lecturer: Hallel Bunis and Elon Rimon ‎
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
25
Thursday
January
2018
Lecture / Seminar
Time: 12:15-13:30
Title: Caging Polygonal Objects Using Minimalistic Three-Finger Hands
Location: Jacob Ziskind Building
Lecturer: Hallel Bunis
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
25
Thursday
January
2018
-
25
Wednesday
January
2108
Lecture / Seminar
Time: 12:15 - 13:30
Title: TBA
Location: Jacob Ziskind Building
Lecturer: Hallel Bunis and Elon Rimon ‎
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
25
Thursday
January
2018
-
25
Wednesday
January
2108
Lecture / Seminar
Time: 12:15 - 13:30
Title: TBA
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
29
Monday
January
2018
Lecture / Seminar
Time: 14:30-16:00
Title: Streaming Symmetric Norms via Measure Concentration
Location: Jacob Ziskind Building
Lecturer: Robert Krauthgamer
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
01
Thursday
February
2018
Lecture / Seminar
Time: 12:15-13:30
Title: TBA
Location: Jacob Ziskind Building
Lecturer: Haggai Marom
Organizer: Faculty of Mathematics and Computer Science

The Chaim Leib Pekeris Memorial Lecture

Date:
07
Wednesday
February
2018
Lecture / Seminar
Time: 11:00-14:55
Title: A Computer Scientist Thinks about the Brain
Lecturer: Professor Christos Papadimitriou
Organizer: Faculty of Mathematics and Computer Science

All Events

Geometric Functional Analysis and Probability Seminar

Date:
18
Thursday
January
2018
Lecture / Seminar
Time: 13:30-15:30
Title: Double Seminar
Location: Jacob Ziskind Building
Lecturer: Oren Louidor (Technion) and Alexander Glazman (Tel Aviv).
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
18
Thursday
January
2018
Lecture / Seminar
Time: 12:15-13:30
Title: One-Sided Unsupervised Domain Mapping via Distance Correlations
Location: Jacob Ziskind Building
Lecturer: Sagie Benaim
Organizer: Faculty of Mathematics and Computer Science

Guest Seminar

Date:
18
Thursday
January
2018
Lecture / Seminar
Time: 11:00-12:00
Title: Automated Verification of Infinite-State Systems with Certifiable Algorithms
Location: Jacob Ziskind Building
Lecturer: Shaull Almagor
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
17
Wednesday
January
2018
Lecture / Seminar
Time: 11:15-12:45
Title: Semisimplification of tensor categories
Location: Jacob Ziskind Building
Lecturer: Pavel Etingof
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
15
Monday
January
2018
Lecture / Seminar
Time: 14:30-16:00
Title: Distributed Computing Made Secure: A New Cycle Cover Theorem
Location: Jacob Ziskind Building
Lecturer: Eylon Yogev
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
11
Thursday
January
2018
Lecture / Seminar
Time: 12:15-13:30
Title: Computational Challenges and Algorithms in Planning for Robotic Systems
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
11
Thursday
January
2018
Lecture / Seminar
Time: 12:15-13:30
Title: Computational Challenges and Algorithms in Planning for Robotic Systems
Location: Jacob Ziskind Building
Lecturer: Oren Salzman
Organizer: Faculty of Mathematics and Computer Science

Machine Learning and Statistics Seminar

Date:
10
Wednesday
January
2018
Lecture / Seminar
Time: 11:15-12:30
Title: Understanding Internal Representations in Deep Learning Models for Language and Speech Processing
Location: Jacob Ziskind Building
Lecturer: Yonatan Belinkov
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
09
Tuesday
January
2018
Lecture / Seminar
Time: 11:15-12:30
Title: Correlation between primes in short intervals on curves over finite fields
Location: Jacob Ziskind Building
Lecturer: Efrat Bank
Organizer: Faculty of Mathematics and Computer Science
Abstract: In this talk, I present an analogue of the Hardy-Littlewood conjecture on the as ...In this talk, I present an analogue of the Hardy-Littlewood conjecture on the asymptotic distribution of prime constellations in the setting of short intervals in function fields of smooth projective curves over finite fields. I will discuss the definition of a "short interval" on a curve as an additive translation of the space of global sections of a sufficiently positive divisor E by a suitable rational function f, and show how this definition generalizes the definition of a short interval in the polynomial setting. I will give a sketch of the proof which includes a computation of a certain Galois group, and a counting argument, namely, Chebotarev density type theorem. This is a joint work with Tyler Foster.

Foundations of Computer Science Seminar

Date:
08
Monday
January
2018
Lecture / Seminar
Time: 14:30-16:00
Title: Cryptography Outside the Black Box
Location: Jacob Ziskind Building
Lecturer: Omer Paneth
Organizer: Faculty of Mathematics and Computer Science

Geometric Functional Analysis and Probability Seminar

Date:
04
Thursday
January
2018
Lecture / Seminar
Time: 13:30-16:00
Title: Double Seminar
Location: Jacob Ziskind Building
Lecturer: Sebastien Bubeck (Microsoft Research) and Percy Deift (Courant Institute)
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
03
Wednesday
January
2018
Lecture / Seminar
Time: 11:15-12:30
Title: Characters of inadmissible representations
Location: Jacob Ziskind Building
Lecturer: Dmitry Vaintrob
Organizer: Faculty of Mathematics and Computer Science

Seminar in Geometry and Topology

Date:
02
Tuesday
January
2018
Lecture / Seminar
Time: 16:15-18:00
Title: The Mean Curvature flow and its applications
Location: Jacob Ziskind Building
Lecturer: Or Hershkovits
Organizer: Faculty of Mathematics and Computer Science

Mathematical Analysis and Applications Seminar

Date:
02
Tuesday
January
2018
Lecture / Seminar
Time: 11:15-12:30
Title: Soft extrapolation of band-limited functions
Location: Jacob Ziskind Building
Lecturer: Dima Batenkov
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
02
Tuesday
January
2018
Lecture / Seminar
Time: 11:15-12:30
Title: Higher Hall algebras
Location: Jacob Ziskind Building
Lecturer: Adam Gal
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
01
Monday
January
2018
Lecture / Seminar
Time: 14:30-16:00
Title: Using the PIR Heuristic to Enhance Secrecy
Location: Jacob Ziskind Building
Lecturer: Yael Tauman Kalai
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
31
Sunday
December
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Dynamic graph matching and related problems
Location: Elaine and Bram Goldsmith Building for Mathematics and Computer Sciences
Lecturer: Shay Solomon
Organizer: Faculty of Mathematics and Computer Science

The National Mathematical Olympiad in memory of Prof. Joseph Gillis

Date:
31
Sunday
December
2017
Lecture / Seminar
Time: 11:00-16:00
Organizer: Faculty of Mathematics and Computer Science

Geometric Functional Analysis and Probability Seminar

Date:
28
Thursday
December
2017
Lecture / Seminar
Time: 13:30-15:30
Title: DOUBLE TALK
Location: Jacob Ziskind Building
Lecturer: Amir Dembo (Stanford) and Yuval Peres (Microsoft)
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
28
Thursday
December
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Discriminability loss for learning to generate descriptive image captions
Location: Jacob Ziskind Building
Lecturer: Greg Shakhnarovich
Organizer: Faculty of Mathematics and Computer Science
Abstract: TBA ...TBA

Algebraic Geometry and Representation Theory Seminar

Date:
27
Wednesday
December
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Generalized Harish-Chandra functors for general linear groups over nite local rings
Location: Jacob Ziskind Building
Lecturer: Ehud Meir
Organizer: Faculty of Mathematics and Computer Science

Distinguished Lecturer

Date:
26
Tuesday
December
2017
Lecture / Seminar
Time: 12:30-13:30
Title: Steady Water Waves
Location: Jacob Ziskind Building
Lecturer: Walter Strauss
Organizer: Faculty of Mathematics and Computer Science
Abstract: The mathematical study of water waves became possible after the derivation of t ...The mathematical study of water waves became possible after the derivation of the basic mathematical equations of fluids by Euler in 1752. Later, water waves, with a free boundary at the air interface, played a central role in the work of Poisson, Cauchy, Stokes, Levi-Civita and many others. It has seen greatly renewed interest among mathematicians in recent years. I will consider classical 2D traveling water waves with vorticity. By means of local and global bifurcation theory using topological degree, one can prove that there exist many such waves. They are exact smooth solutions of the Euler equations with the physical boundary conditions. Some of the waves are quite tall and steep and some are overhanging. There are periodic ones and solitary ones. I will also exhibit some numerical computations of such waves. Many fundamental problems remain open.

Distinguished Lecturer

Date:
26
Tuesday
December
2017
Lecture / Seminar
Time: 11:15-12:15
Title: Optimal Mass Transport and the Robustness of Complex Networks
Location: Jacob Ziskind Building
Lecturer: Allen Tannenbaum
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
26
Tuesday
December
2017
Lecture / Seminar
Time: 11:15-11:30
Title: Algebraic Families of Harish-Chandra Modules and their Application
Location: Jacob Ziskind Building
Lecturer: Eyal Subag
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
25
Monday
December
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Prediction from Partial Information and Hindsight, with Application to Circuit Lower Bounds
Location: Jacob Ziskind Building
Lecturer: Or Meir
Organizer: Faculty of Mathematics and Computer Science
Abstract: Consider a random sequence of n bits that has entropy at least n-k, where k ...Consider a random sequence of n bits that has entropy at least n-k, where k

Foundations of Computer Science Seminar

Date:
25
Monday
December
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Prediction from Partial Information and Hindsight, with Application to Circuit Lower Bounds
Location: Jacob Ziskind Building
Lecturer: Or Meir
Organizer: Faculty of Mathematics and Computer Science

Geometric Functional Analysis and Probability Seminar

Date:
21
Thursday
December
2017
Lecture / Seminar
Time: 13:30-15:30
Title: CLT for small scale mass distribution of toral Laplace eigenfunctions
Location: Jacob Ziskind Building
Lecturer: Nadav Yesha
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
21
Thursday
December
2017
Lecture / Seminar
Time: 12:15-13:30
Title: “Zero-Shot” Super-Resolution using Deep Internal Learning
Location: Jacob Ziskind Building
Lecturer: Assaf Shocher
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
20
Wednesday
December
2017
Lecture / Seminar
Time: 11:15-12:30
Title: A Bavula conjecture
Location: Jacob Ziskind Building
Lecturer: Lenny Makar-Limanov
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
19
Tuesday
December
2017
Lecture / Seminar
Time: 11:15-12:30
Title: L-function of cuspidal representations of G_2 and their poles
Location: Jacob Ziskind Building
Lecturer: Avner Segal
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
18
Monday
December
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Improved Pseudorandomness for Unordered Branching Programs through Local Monotonicity
Location: Jacob Ziskind Building
Lecturer: Avishay Tal
Organizer: Faculty of Mathematics and Computer Science

Machine Learning and Statistics Seminar

Date:
13
Wednesday
December
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Overcoming Intractability in Learning
Location: Jacob Ziskind Building
Lecturer: Roi Livni
Organizer: Faculty of Mathematics and Computer Science

Seminar in Geometry and Topology

Date:
12
Tuesday
December
2017
Lecture / Seminar
Time: 16:15-17:30
Title: Tempered Manifolds and Schwartz Functions on Them
Location: Jacob Ziskind Building
Lecturer: Ary Shaviv
Organizer: Faculty of Mathematics and Computer Science
Abstract: Schwartz functions are classically defined as smooth functions such that they, a ...Schwartz functions are classically defined as smooth functions such that they, and all their (partial) derivatives, decay at infinity faster than the inverse of any polynomial. This was formulated on $mathbb{R}^n$ by Laurent Schwartz, and later on Nash manifolds (smooth semi-algebraic varieties) by Fokko du Cloux and by Rami Aizenbud and Dima Gourevitch. In a joint work with Boaz Elazar we have extended the theory of Schwartz functions to the category of (possibly singular) real algebraic varieties. The basic idea is to define Schwartz functions on a (closed) algebraic subset of $mathbb{R}^n$ as restrictions of Schwartz functions on $mathbb{R}^n$. Both in the Nash and the algebraic categories there exists a very useful characterization of Schwartz functions on open subsets, in terms of Schwartz functions on the embedding space: loosely speaking, Schwartz functions on an open subset are exactly restrictions of Schwartz functions on the embedding space, which are zero "to infinite order" on the complement to this open subset. This characterization suggests a very intuitive way to attach a space of Schwartz functions to an arbitrary (not necessarily semi-algebraic) open subset of $mathbb{R}^n$. In this talk, I will explain this construction, and more generally the construction of the category of tempered smooth manifolds. This category is in a sense the "largest" category whose objects "look" locally like open subsets of $mathbb{R}^n$ (for some $n$), and on which Schwartz functions may be defined. In the development of this theory some classical results of Whitney are used, mainly Whitney type partition of unity (this will also be explained in the talk). As time permits, I will show some properties of Schwartz functions, and describe some possible applications. This is a work in progress.

Foundations of Computer Science Seminar

Date:
11
Monday
December
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Interplays between Machine Learning and Optimization
Location: Jacob Ziskind Building
Lecturer: Tomer Koren
Organizer: Faculty of Mathematics and Computer Science

Geometric Functional Analysis and Probability Seminar

Date:
07
Thursday
December
2017
Lecture / Seminar
Time: 13:30-15:30
Title: Discontinuity of the phase transition for the planar random-cluster and Potts models with $q > 4$
Location: Jacob Ziskind Building
Lecturer: Matan Harel
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
07
Thursday
December
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Temporal Tessellation: A Unified Approach for Video Analysis
Location: Jacob Ziskind Building
Lecturer: Dotan Kaufman
Organizer: Faculty of Mathematics and Computer Science

Mathematical Analysis and Applications Seminar

Date:
05
Tuesday
December
2017
Lecture / Seminar
Time: 11:15-12:15
Title: Spectral asymptotic for Steklov’s problem in domains with edges (work in progress)
Location: Jacob Ziskind Building
Lecturer: Victor Ivrii
Organizer: Faculty of Mathematics and Computer Science
Abstract: We derive sharp eigenvalue asymptotics for Dirichlet-to-Neumann operator in the ...We derive sharp eigenvalue asymptotics for Dirichlet-to-Neumann operator in the domain with edges and discuss obstacle for deriving the second term

Vision and Robotics Seminar

Date:
05
Tuesday
December
2017
Lecture / Seminar
Time: 11:00-12:30
Title: Geometry Processing Methods and Their Real-Life Applications
Location: Jacob Ziskind Building
Lecturer: Amit Bermano
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
04
Monday
December
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Practical Locally Private Heavy Hitters
Location: Jacob Ziskind Building
Lecturer: Uri Stemmer
Organizer: Faculty of Mathematics and Computer Science

Geometric Functional Analysis and Probability Seminar

Date:
30
Thursday
November
2017
Lecture / Seminar
Time: 13:30-15:30
Title: Large deviations principles for random matrices
Location: Jacob Ziskind Building
Lecturer: Fanny Augeri
Organizer: Faculty of Mathematics and Computer Science

Machine Learning and Statistics Seminar

Date:
29
Wednesday
November
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Inverse Problems and Unsupervised Learning with applications to Cryo-Electron Microscopy (cryo-EM)
Location: Jacob Ziskind Building
Lecturer: Roy Lederman
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
28
Tuesday
November
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Weyl group multiple Dirichlet series
Location: Jacob Ziskind Building
Lecturer: Yuanqing Cai
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
27
Monday
November
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Informational Bounds on Approximate Nash Equilibria
Location: Jacob Ziskind Building
Lecturer: Yakov Babichenko
Organizer: Faculty of Mathematics and Computer Science
Abstract: ...

Geometric Functional Analysis and Probability Seminar

Date:
23
Thursday
November
2017
Lecture / Seminar
Time: 14:10-16:00
Title: Persistence of Gaussian Stationary Processes
Location: Jacob Ziskind Building
Lecturer: Naomi Feldheim
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
23
Thursday
November
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Seeing Through Noise: Visually Driven Speaker Separation and Enhancement
Location: Jacob Ziskind Building
Lecturer: Aviv Gabbay
Organizer: Faculty of Mathematics and Computer Science
Abstract: ...

Special Guest Lecture

Date:
22
Wednesday
November
2017
Lecture / Seminar
Time: 16:15-18:00
Title: The pressure function for infinite equilibrium
Location: Jacob Ziskind Building
Lecturer: Dalia Terhesiu
Organizer: Faculty of Mathematics and Computer Science

Special Guest Lecture

Date:
22
Wednesday
November
2017
Lecture / Seminar
Time: 16:15-18:00
Title: The pressure function for infinite equilibrium
Location: Jacob Ziskind Building
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
22
Wednesday
November
2017
Lecture / Seminar
Time: 11:15-12:30
Title: About Index of Lie Algebras
Location: Jacob Ziskind Building
Lecturer: Alexander Elashvili
Organizer: Faculty of Mathematics and Computer Science
Abstract: In my talk I plan to give overview of results about of index of biparaboic subal ...In my talk I plan to give overview of results about of index of biparaboic subalgebras of classical Lie algebras and formulate conjecture about asymptotic biheviar of lieandric numbers.

Algebraic Geometry and Representation Theory Seminar

Date:
21
Tuesday
November
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Uniform p-adic integration and applications
Location: Jacob Ziskind Building
Lecturer: Raf Cluckers
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
15
Wednesday
November
2017
Lecture / Seminar
Time: 14:15-16:00
Title: Injective modules in higher algebra
Location: Jacob Ziskind Building
Lecturer: Liran Shaul
Organizer: Faculty of Mathematics and Computer Science
Abstract: The notion of an Injective module is one of the most fundamental notions in hom ...The notion of an Injective module is one of the most fundamental notions in homological algebra over rings. In this talk, we explain how to generalize this notion to higher algebra. The Bass-Papp theorem states that a ring is left noetherian if and only if an arbitrary direct sum of left injective modules is injective. We will explain a version of this result in higher algebra, which will lead us to the notion of a left noetherian derived ring. In the final part of the talk, we will specialize to commutative noetherian rings in higher algebra, show that the Matlis structure theorem of injective modules generalize to this setting, and explain how to deduce from it a version of Grothendieck's local duality theorem over commutative noetherian local DG rings.

Machine Learning and Statistics Seminar

Date:
15
Wednesday
November
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Group Symmetric Robust Covariance Estimation
Location: Jacob Ziskind Building
Lecturer: Ilya Soloveychik
Organizer: Faculty of Mathematics and Computer Science
Abstract: Covariance matrix estimation is essential in many areas of modern Statistics and ...Covariance matrix estimation is essential in many areas of modern Statistics and Machine Learning including Graphical Models, Classification/Discriminant Analysis, Principal Component Analysis, and many others. Classical statistics suggests using Sample Covariance Matrix (SCM) which is a Maximum Likelihood Estimator (MLE) in the Gaussian populations. Real world data, however, usually exhibits heavy-tailed behavior and/or contains outliers, making the SCM non-efficient or even useless. This problem and many similar ones gave rise to the Robust Statistics field in early 60s, where the main goal was to develop estimators stable under reasonable deviations from the basic Gaussian assumptions. One of the most prominent robust covariance matrix estimators was introduced and thoroughly studied by D. Tyler in the mid-80s. This important representative of the family of M-estimators can be defined as an MLE of a certain population. The problem of robust covariance estimation becomes even more involved in the high-dimensional scenario, where the number of samples n is of the order of the dimension p, or even less. In such cases, prior knowledge, often referred to as structure, is utilized to decrease the number of degrees of freedom and make the estimation possible. Unlike the Gaussian setting, in Tyler's case even imposition of linear structure becomes challenging due to the non-convexity of the negative log-likelihood. Recently, Tyler’s target function was shown to become convex under a certain change of metric (geodesic convexity), which stimulated further investigation of the estimator. In this work, we focus on the so-called group symmetry structure, which essentially means that the true covariance matrix commutes with a group of unitary matrices. In engineering applications such structures appear due to the natural symmetries of the physical processes

Distinguished Lecturer

Date:
14
Tuesday
November
2017
Lecture / Seminar
Time: 11:15-12:15
Title: The Dynamical Systems Approach to Coupled Map Lattices
Location: Jacob Ziskind Building
Lecturer: Prof. Yakov Pesin
Organizer: Faculty of Mathematics and Computer Science
Abstract: Coupled Map Lattices (CML) of an unbounded media appear as a result of time and ...Coupled Map Lattices (CML) of an unbounded media appear as a result of time and space discretization of evolutional partial differential equations but can also be viewed as original phenomenological models of the medium. I will present the dynamical systems approach to study the global behavior of solutions of CML. In particular, I will describe the dynamics of the evolution operator on the set of traveling wave solutions of CML and discuss the phenomenon known as spatio-temporal chaos. I will illustrate this phenomenon in the particular example of CML associated with the famous FitzHue-Nagumo equation that describes propagation of voltage impulse through a nerve axon. When the leading parameter of this equation varies the dynamics undergoes several stages presenting Morse-Smale type dynamics, strange attractors and Smale horseshoes.

Foundations of Computer Science Seminar

Date:
13
Monday
November
2017
Lecture / Seminar
Time: 14:30-16:00
Title: The Adaptive Complexity of Maximizing a Submodular Function
Location: Jacob Ziskind Building
Lecturer: Eric Balkanski
Organizer: Faculty of Mathematics and Computer Science

Geometric Functional Analysis and Probability Seminar

Date:
09
Thursday
November
2017
Lecture / Seminar
Time: 14:00-16:00
Title: Real and complex eigenvalues of the non-self-adjoint Anderson model.
Location: Jacob Ziskind Building
Lecturer: Ilya Goldsheid
Organizer: Faculty of Mathematics and Computer Science
Abstract: TBA ...TBA

Foundations of Computer Science Seminar

Date:
06
Monday
November
2017
Lecture / Seminar
Time: 14:30-16:00
Title: New Results on Learning and Reconstruction of Quantum States
Location: Jacob Ziskind Building
Lecturer: Scott Aaronson
Organizer: Faculty of Mathematics and Computer Science
Abstract: ...

Algebraic Geometry and Representation Theory Seminar

Date:
31
Tuesday
October
2017
Lecture / Seminar
Time: 11:15-12:30
Title: The non-Archimedean Monge-Ampere problem
Location: Jacob Ziskind Building
Lecturer: Walter Gubler
Organizer: Faculty of Mathematics and Computer Science
Abstract: ...

Geometry and Topology Seminar

Date:
17
Tuesday
October
2017
Lecture / Seminar
Time: 16:15-17:15
Title: Holography of traversing flows and its applications to the inverse scattering problems
Location: Jacob Ziskind Building
Lecturer: Gabriel Katz
Organizer: Faculty of Mathematics and Computer Science
Abstract: We study the non-vanishing gradient-like vector fields $v$ on smooth compact man ...We study the non-vanishing gradient-like vector fields $v$ on smooth compact manifolds $X$ with boundary. We call such fields traversing. With the help of a boundary generic field $v$, we divide the boundary $d X$ of $X$ into two complementary compact manifolds, $d^ X(v)$ and $d^-X(v)$. Then we introduce the causality map $C_v: d^ X(v) o d^-X(v)$, a distant relative of the Poincare return map. Let $mathcal F(v)$ denote the oriented 1-dimensional foliation on $X$, produced by a traversing $v$-flow. Our main result, the Holography Theorem, claims that, for boundary generic traversing vector fields $v$, the knowledge of the causality map $C_v$ is allows for a reconstruction of the pair $(X, mathcal F(v))$, up to a homeomorphism $Phi: X o X$ which is the identity on the boundary $d X$. In other words, for a massive class of ODE's, we show that the topology of their solutions, satisfying a given boundary value problem, is rigid. We call these results ``holographic" since the $(n 1)$-dimensional $X$ and the un-parameterized dynamics of the flow on it are captured by a single correspondence $C_v$ between two $n$-dimensional screens, $d^ X(v)$ and $d^-X(v)$. This holography of traversing flows has numerous applications to the dynamics of general flows. Time permitting, we will discuss some applications of the Holography Theorem to the geodesic flows and the inverse scattering problems on Riemannian manifolds with boundary.

Faculty Summer Event

Date:
14
Thursday
September
2017
Retreat
Time: 18:30-22:00
Location: Campus Recreation Center
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
06
Wednesday
September
2017
Lecture / Seminar
Time: 11:35-12:30
Location: Jacob Ziskind Building
Lecturer: Thorsten Heidersdorf
Organizer: Faculty of Mathematics and Computer Science
Abstract: Abstract: Let Rep(GL(m|n)) denote the category of finite-dimensional algebraic r ...Abstract: Let Rep(GL(m|n)) denote the category of finite-dimensional algebraic representations of the supergroup Gl(m|n). Nowadays the abelian structure (Ext^1 between irreducibles, block description,...) is well understood. Kazhdan-Lusztig theory gives an algorithmic solution for the character problem, and in special cases even explicit character formulas. However we understand the monoidal structure hardly at all (e.g. the decomposition of tensor products into the indecomposable constituents). I will talk about the problem of decomposing tensor products "up to superdimension 0", i.e. about the structure of Rep(GL(m|n))N where N is the ideal of indecomposable representations of superdimension 0.

Algebraic Geometry and Representation Theory Seminar

Date:
06
Wednesday
September
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Reductive groups attached to representations of the general linear supergroup GL(m|n)
Location: Jacob Ziskind Building
Lecturer: Thorsten Heidersdorf
Organizer: Faculty of Mathematics and Computer Science
Abstract: Let Rep(GL(m|n)) denote the category of finite-dimensional algebraic representat ...Let Rep(GL(m|n)) denote the category of finite-dimensional algebraic representations of the supergroup Gl(m|n). Nowadays the abelian structure (Ext^1 between irreducibles, block description,...) is well understood. Kazhdan-Lusztig theory gives an algorithmic solution for the character problem, and in special cases even explicit character formulas. However we understand the monoidal structure hardly at all (e.g. the decomposition of tensor products into the indecomposable constituents). I will talk about the problem of decomposing tensor products "up to superdimension 0", i.e. about the structure of Rep(GL(m|n))/N where N is the ideal of indecomposable representations of superdimension 0.

Vision and Robotics Seminar

Date:
04
Monday
September
2017
Lecture / Seminar
Time: 14:00-15:00
Title: Hand-object interaction: a step towards action recognition
Location: Jacob Ziskind Building
Lecturer: Ita Lifshitz
Organizer: Faculty of Mathematics and Computer Science
Abstract: When dealing with a highly variable problem such as action recognition, focusing ...When dealing with a highly variable problem such as action recognition, focusing on a small area, such as the hand's region, makes the problem more manageable, and enables us to invest relatively high amount of resources needed for interpretation in a small but highly informative area of the image. In order to detect this region of interest in the image and properly analyze it, I have built a process that includes several steps, starting with a state of the art hand detector, incorporating both detection of the hand by appearance and by estimation of human body pose. The hand detector is built upon a fully convolutional neural network, detecting hands efficiently and accurately. The human body pose estimation starts with a state of the art head detector and continues with a novel approach where each location in the image votes for the position of each body keypoint, utilizing information from the whole image. Using dense, multi-target votes enables us to compute image-dependent joint keypoint probabilities by looking at consensus voting, and accurately estimates the body pose. Once the detection of the hands is complete, an additional step of segmentation of the hand and fingers is made. In this step each hand pixel in the image is labeled using a dense fully convolutional network. Finally, an additional step is made to segment and identify the held object. Understanding the hand-object interaction is an important step toward understanding the action taking place in the image. These steps enable us to perform fine interpretation of hand-object interaction images as an essential step towards understanding the human-object interaction and recognizing human activities.

Algebraic Geometry and Representation Theory Seminar

Date:
11
Tuesday
July
2017
Lecture / Seminar
Time: 11:15-12:30
Title: The uncovering of fibers’ Mumford system
Location: Elaine and Bram Goldsmith Building for Mathematics and Computer Sciences
Lecturer: Jasmine Fittouhi
Organizer: Faculty of Mathematics and Computer Science
Abstract: This talk is dedicate to the description of the fibers resulting from the Mumfor ...This talk is dedicate to the description of the fibers resulting from the Mumford system of degree g>0. Each fiber is linked to a hyperelliptic curve

Foundations of Computer Science Seminar

Date:
10
Monday
July
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Derandomizing Isolation Lemma: a geometric approach
Location: Jacob Ziskind Building
Lecturer: Rohit Gurjar
Organizer: Faculty of Mathematics and Computer Science
Abstract: We present a geometric approach towards derandomizing the Isolation lemma for a ...We present a geometric approach towards derandomizing the Isolation lemma for a given family, i.e., deterministically constructing a weight assingnment which ensures a unique minimum weight set in the family. The idea is to work with a polytope corresponding to the family of sets. In this talk, we present the approach in terms of general polytopes and describe a sufficient condition on the polytope for this approach to work. The approach gives a quasi-polynomially bounded weight assignment. Finally, we show that two specific families - perfect matchings in bipartite graphs and common base sets of two matroids - satisfy the required condition and thus, we get an isolating weight assignment for these cases. This also puts the two problems in quasi-NC. Based on joint works with Stephen Fenner and Thomas Thierauf.

Vision and Robotics Seminar

Date:
06
Thursday
July
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Big data - small training sets: biomedical image analysis bottlenecks, some strategies and applications
Location: Jacob Ziskind Building
Lecturer: Tammy Riklin-Raviv
Organizer: Faculty of Mathematics and Computer Science
Abstract: TBN ...TBN

Machine Learning and Statistics Seminar

Date:
05
Wednesday
July
2017
Lecture / Seminar
Time: 11:15-12:15
Title: Common Manifold Learning with Alternating Diffusion
Location: Jacob Ziskind Building
Lecturer: Ronen Talmon
Organizer: Faculty of Mathematics and Computer Science

Mathematical Analysis and Applications Seminar

Date:
04
Tuesday
July
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Some remarks about Fractional Laplacian in connection with kinetic theory
Location: Jacob Ziskind Building
Lecturer: Claude Bardos
Organizer: Faculty of Mathematics and Computer Science
Abstract: This talk will contain some remarks on the different aspects of the fractional ...This talk will contain some remarks on the different aspects of the fractional Laplacian and a derivation of fractional diffusion from Kinetic Models inspired by the work of Mellet and illustrated by an example of Uriel and Helene Frisch on radiative transfert which goes back to 1977.

Foundations of Computer Science Seminar

Date:
03
Monday
July
2017
Lecture / Seminar
Time: 14:30-16:30
Title: Crossing the Logarithmic Barrier for Dynamic Boolean Data Structure Lower Bounds
Location: Jacob Ziskind Building
Lecturer: Omri Weinstein
Organizer: Faculty of Mathematics and Computer Science
Abstract: We prove the first super-logarithmic lower bounds on the cell probe complexity o ...We prove the first super-logarithmic lower bounds on the cell probe complexity of dynamic *boolean* (a.k.a. decision) data structure problems, a long-standing milestone in data structure lower bounds. We introduce a new technique and use it to prove a ~ log^{1.5}(n) lower bound on the operational time of a wide range of boolean data structure problems, most notably, on the query time of dynamic range counting *over F_2* ([Patrascu07]). Proving a super-logarithmic lower bound for this problem was explicitly posed as one of five important open problems in the late Mihai Patrascu's obituary [Tho13]. This result also implies the first super-logarithmic lower bound for the classical 2D range counting problem,one of the most fundamental data structure problems in computational geometry and spatial databases. We derive similar lower bounds for boolean versions of dynamic polynomial evaluation and 2D "rectangle stabbing", and for the (non-boolean) problems of range selection and range median. Our technical centerpiece is a new way of "weakly" simulating dynamic data structures using efficient *one-way* communication protocols with small advantage over random guessing. This simulation involves a surprising excursion to low-degree (Chebychev) polynomials which may be of independent interest, and offers an entirely new algorithmic angle on the "cell sampling" method of Panigrahy et al. [PTW10]. Joint work with Kasper Green-Larsen and Huacheng Yu.

Vision and Robotics Seminar

Date:
29
Thursday
June
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Co-occurrence Filter
Location: Jacob Ziskind Building
Lecturer: Shai Avidan
Organizer: Faculty of Mathematics and Computer Science
Abstract: Co-occurrence Filter (CoF) is a boundary preserving filter. It is based on the B ...Co-occurrence Filter (CoF) is a boundary preserving filter. It is based on the Bilateral Filter (BF) but instead of using a Gaussian on the range values to preserve edges it relies on a co-occurrence matrix. Pixel values that co-occur frequently in the image (i.e., inside textured regions) will have a high weight in the co-occurrence matrix. This, in turn, means that such pixel pairs will be averaged and hence smoothed, regardless of their intensity differences. On the other hand, pixel values that rarely co-occur (i.e., across texture boundaries) will have a low weight in the co-occurrence matrix. As a result, they will not be averaged and the boundary between them will be preserved. The CoF therefore extends the BF to deal with boundaries, not just edges. It learns co-occurrences directly from the image. We can achieve various filtering results by directing it to learn the co-occurrence matrix from a part of the image, or a different image. We give the definition of the filter, discuss how to use it with color images and show several use cases. Joint work with Roy Jevnisek

Geometric Functional Analysis and Probability Seminar

Date:
29
Thursday
June
2017
Lecture / Seminar
Time: 11:15-13:00
Title: The criticality of a randomly-driven front.
Location: Jacob Ziskind Building
Lecturer: Amir Dembo
Organizer: Faculty of Mathematics and Computer Science
Abstract: Consider independent continuous-time random walks on the integers to the right o ...Consider independent continuous-time random walks on the integers to the right of a front R(t). Starting at R(0)=0, whenever a particle attempts to jump into the front, the latter instantaneously advances k steps to the right, absorbing all particles along its path. Sly (2016) resolves the question of Kesten and Sidoravicius (2008), by showing that for k=1 the front R(t) advances linearly once the particle density exceeds 1, but little is known about the large t asymptotic of R(t) at critical density 1. In a joint work with L-C Tsai, for the variant model with k taken as the minimal random integer such that exactly k particles are absorbed by the move of R(t), we obtain both scaling exponent and the random scaling limit for the front at the critical density 1. Our result unveils a rarely seen phenomenon where the macroscopic scaling exponent is sensitive to the initial local fluctuations (with the scaling limit oscillating between instantaneous super and sub-critical phases).

Foundations of Computer Science Seminar

Date:
26
Monday
June
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Randomized Online Matching in Regular Graphs
Location: Jacob Ziskind Building
Lecturer: Ilan Cohen
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
22
Thursday
June
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Convolutional Neural Networks on Surfaces via Seamless Toric Covers
Location: Jacob Ziskind Building
Lecturer: Haggai Maron
Organizer: Faculty of Mathematics and Computer Science
Abstract: The recent success of convolutional neural networks (CNNs) for image processing ...The recent success of convolutional neural networks (CNNs) for image processing tasks is inspiring research efforts attempting to achieve similar success for geometric tasks. One of the main challenges in applying CNNs to surfaces is defining a natural convolution operator on surfaces In this paper we present a method for applying deep learning to sphere-type shapes using a global seamless parameterization to a planar flat-torus, for which the convolution operator is well defined. As a result, the standard deep learning framework can be readily applied for learning semantic, high-level properties of the shape. An indication of our success in bridging the gap between images and surfaces is the fact that our algorithm succeeds in learning semantic information from an input of raw low-dimensional feature vectors. We demonstrate the usefulness of our approach by presenting two applications: human body segmentation, and automatic landmark detection on anatomical surfaces. We show that our algorithm compares favorably with competing geometric deep-learning algorithms for segmentation tasks, and is able to produce meaningful correspondences on anatomical surfaces where hand-crafted features are bound to fail. Joint work with: Meirav Galun, Noam Aigerman, Miri Trope, Nadav Dym, Ersin Yumer, Vladimir G. Kim and Yaron Lipman.

Machine Learning and Statistics Seminar

Date:
21
Wednesday
June
2017
Lecture / Seminar
Time: 11:15-12:30
Title: On the relationship between structure in the data and what deep learning can learn
Location: Jacob Ziskind Building
Lecturer: Raja Giryes
Organizer: Faculty of Mathematics and Computer Science
Abstract: The past five years have seen a dramatic increase in the performance of recognit ...The past five years have seen a dramatic increase in the performance of recognition systems due to the introduction of deep architectures for feature learning and classification. However, the mathematical reasons for this success remain elusive. In this talk we will briefly survey some existing theory of deep learning. In particular, we will focus on data structure based theory and discuss two recent developments. The first work studies the generalization error of deep neural network. We will show how the generalization error of deep networks can be bounded via their classification margin. We will also discuss the implications of our results for the regularization of the networks. For example, the popular weight decay regularization guarantees the margin preservation, but it leads to a loose bound to the classification margin. We show that a better regularization strategy can be obtained by directly controlling the properties of the network's Jacobian matrix. The second work focuses on solving minimization problems with neural networks. Relying on recent recovery techniques developed for settings in which the desired signal belongs to some low-dimensional set, we show that using a coarse estimate of this set leads to faster convergence of certain iterative algorithms with an error related to the accuracy of the set approximation. Our theory ties to recent advances in sparse recovery, compressed sensing and deep learning. In particular, it provides an explanation for the successful approximation of the ISTA (iterative shrinkage and thresholding algorithm) solution by neural networks with layers representing iterations. Joint work with Guillermo Sapiro, Miguel Rodrigues, Jure Sokolic, Alex Bronstein and Yonina Eldar.

Algebraic Geometry and Representation Theory Seminar

Date:
20
Tuesday
June
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Revisiting vanishing cycles and duality in étale cohomology
Location: Jacob Ziskind Building
Lecturer: Luc Illusie
Organizer: Faculty of Mathematics and Computer Science
Abstract: Abstract: In the early 1980's Gabber proved compatibility of nearby cycles with ...Abstract: In the early 1980's Gabber proved compatibility of nearby cycles with duality and Beilinson compatibility of vanishing cycles with duality. I will explain new insights and results on this topic, due to Beilinson, Gabber, and Zheng.

Vision and Robotics Seminar

Date:
15
Thursday
June
2017
Lecture / Seminar
Time: 12:15-13:30
Title: On Learning Invariants and Representation Spaces of Shapes and Forms
Location: Jacob Ziskind Building
Lecturer: Ron Kimmel
Organizer: Faculty of Mathematics and Computer Science
Abstract: We study the power of the Laplace Beltrami Operator (LBO) in processing and anal ...We study the power of the Laplace Beltrami Operator (LBO) in processing and analyzing geometric information. The decomposition of the LBO at one end, and the heat operator at the other end provide us with efficient tools for dealing with images and shapes. Denoising, segmenting, filtering, exaggerating are just few of the problems for which the LBO provides an efficient solution. We review the optimality of a truncated basis provided by the LBO, and a selection of relevant metrics by which such optimal bases are constructed. Specific example is the scale invariant metric for surfaces that we argue to be a natural selection for the study of articulated shapes and forms. In contrast to geometry understanding there is a new emerging field of deep learning. Learning systems are rapidly dominating the areas of audio, textual, and visual analysis. Recent efforts to convert these successes over to geometry processing indicate that encoding geometric intuition into modeling, training, and testing is a non-trivial task. It appears as if approaches based on geometric understanding are orthogonal to those of data-heavy computational learning. We propose to unify these two methodologies by computationally learning geometric representations and invariants and thereby take a small step towards a new perspective on geometry processing. I will present examples of shape matching, facial surface reconstruction from a single image, reading facial expressions, shape representation, and finally definition and computation of invariant operators and signatures.

Geometric Functional Analysis and Probability Seminar

Date:
15
Thursday
June
2017
Lecture / Seminar
Time: 11:15-13:00
Title: Gaussian mixtures with applications to entropy inequalities and convex geometry
Location: Jacob Ziskind Building
Lecturer: Piotr Nayar
Organizer: Faculty of Mathematics and Computer Science
Abstract: We say that a symmetric random variable X is a Gaussian mixture if X has the sam ...We say that a symmetric random variable X is a Gaussian mixture if X has the same distribution as YG, where G is a standard Gaussian random variable, and Y is a positive random variable independent of G. In the first part of the talk we use this simple notion to study the Shannon entropy of sums of independent random variables. In the second part we investigate, using Gaussian mixtures, certain topics related to the geometry of B_p^n balls, including optimal Khinchine-type inequalities and Schur-type comparison for volumes of section and projections of these sets. In the third part we discuss extensions of Gaussian correlation inequality to the case of p-stable laws and uniform measure on the Euclidean sphere. Based on a joint work with Alexandros Eskenazis and Tomasz Tkocz.

Foundations of Computer Science Seminar

Date:
15
Thursday
June
2017
Lecture / Seminar
Time: 11:00-13:00
Title: Computational Social Choice: For the People
Location: Jacob Ziskind Building
Lecturer: Ariel Procaccia
Organizer: Faculty of Mathematics and Computer Science
Abstract: Computational social choice deals with algorithms for aggregating individual pre ...Computational social choice deals with algorithms for aggregating individual preferences or opinions towards collective decisions. AI researchers (including myself) have long argued that such algorithms could play a crucial role in the design and implementation of multiagent systems. However, in the last few years I have come to realize that the "killer app" of computational social choice is helping people -- not software agents -- make joint decisions. I will illustrate this theme through two recent endeavors: Spliddit.org, a website that offers provably fair solutions to everyday problems

Vision and Robotics Seminar

Date:
08
Thursday
June
2017
Lecture / Seminar
Time: 12:15-13:45
Title: Expressive Efficiency and Inductive Bias of Convolutional Networks: Analysis and Design through Hierarchical Tensor Decompositions
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
08
Thursday
June
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Expressive Efficiency and Inductive Bias of Convolutional Networks: Analysis and Design through Hierarchical Tensor Decompositions
Location: Jacob Ziskind Building
Lecturer: Nadav Cohen
Organizer: Faculty of Mathematics and Computer Science
Abstract: The driving force behind convolutional networks - the most successful deep learn ...The driving force behind convolutional networks - the most successful deep learning architecture to date, is their expressive power. Despite its wide acceptance and vast empirical evidence, formal analyses supporting this belief are scarce. The primary notions for formally reasoning about expressiveness are efficiency and inductive bias. Efficiency refers to the ability of a network architecture to realize functions that require an alternative architecture to be much larger. Inductive bias refers to the prioritization of some functions over others given prior knowledge regarding a task at hand. Through an equivalence to hierarchical tensor decompositions, we study the expressive efficiency and inductive bias of various architectural features in convolutional networks (depth, width, pooling geometry and more). Our results shed light on the demonstrated effectiveness of convolutional networks, and in addition, provide new tools for network design. The talk is based on a series of works published in COLT, ICML, CVPR and ICLR (as well as several new preprints), with collaborators Or Sharir, Ronen Tamari, David Yakira, Yoav Levine and Amnon Shashua.

Geometric Functional Analysis and Probability Seminar

Date:
08
Thursday
June
2017
Lecture / Seminar
Time: 11:15-13:15
Title: Irrational rotations, random affine transformations and the central limit theorem
Location: Jacob Ziskind Building
Lecturer: Nishant Chandgotia
Organizer: Faculty of Mathematics and Computer Science
Abstract: It is a well-known result from Hermann Weyl that if alpha is an irrational numbe ...It is a well-known result from Hermann Weyl that if alpha is an irrational number in [0,1) then the number of visits of successive multiples of alpha modulo one in an interval contained in [0,1) is proportional to the size of the interval. In this talk we will revisit this problem, now looking at finer joint asymptotics of visits to several intervals with rational end points. We observe that the visit distribution can be modelled using random affine transformations

Geometric Functional Analysis and Probability Seminar

Date:
08
Thursday
June
2017
Lecture / Seminar
Time: 11:15-13:15
Title: Irrational rotations, random affine transformations and the central limit theorem
Location: Jacob Ziskind Building
Lecturer: Nishant Chandgotia
Organizer: Faculty of Mathematics and Computer Science
Abstract: It is a well-known result from Hermann Weyl that if alpha is an irrational numbe ...It is a well-known result from Hermann Weyl that if alpha is an irrational number in [0,1) then the number of visits of successive multiples of alpha modulo one in an interval contained in [0,1) is proportional to the size of the interval. In this talk we will revisit this problem, now looking at finer joint asymptotics of visits to several intervals with rational end points. We observe that the visit distribution can be modelled using random affine transformations

Algebraic Geometry and Representation Theory Seminar

Date:
06
Tuesday
June
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Positivity properties of metrics in non-archimedean geometry
Location: Elaine and Bram Goldsmith Building for Mathematics and Computer Sciences
Lecturer: Klaus Kunnemann
Organizer: Faculty of Mathematics and Computer Science
Abstract: We describe the Calabi-Yau problem on complex manifolds and its analog in non-ar ...We describe the Calabi-Yau problem on complex manifolds and its analog in non-archimedean geometry. We discuss positivity properties of metrics on line bundles over non-archimedean analytic spaces and applications to the solution of the non-archimedean Calabi-Yau problem in the equicharacteristic zero case.

Vision and Robotics Seminar

Date:
01
Thursday
June
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Synchronization over Cartan motion groups
Location: Jacob Ziskind Building
Lecturer: Nir Sharon
Organizer: Faculty of Mathematics and Computer Science
Abstract: The mathematical problem of group synchronization deals with the question of how ...The mathematical problem of group synchronization deals with the question of how to estimate unknown group elements from a set of their mutual relations. This problem appears as an important step in solving many real-world problems in vision, robotics, tomography, and more. In this talk, we present a novel solution for synchronization over the class of Cartan motion groups, which includes the special important case of rigid motions. Our method is based on the idea of group contraction, an algebraic notion origin in relativistic mechanics.

Algebraic Geometry and Representation Theory Seminar

Date:
30
Tuesday
May
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Multivariate Hypergeometric functions with a parameter
Lecturer: Siddhartha Sahi
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
29
Monday
May
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Almost Optimal eps bias
Location: Jacob Ziskind Building
Lecturer: Amnon Ta-Shma
Organizer: Faculty of Mathematics and Computer Science
Abstract: The question of finding an epsilon-biased set with close to optimal support size ...The question of finding an epsilon-biased set with close to optimal support size, or, equivalently, finding an explicit binary code with distance 1/2-epsilon and rate close to the Gilbert-Varshamov bound, attracted a lot of attention in recent decades. In this paper we solve the problem almost optimally and show an explicit epsilon-biased set over k bits with support size O(k/epsilon^{2 o(1)}). This improves upon all previous explicit constructions which were in the order of k^2/epsilon^2, k/epsilon^3 or (k/epsilon^2)^{5/4}. The result is close to the Gilbert-Varshamov bound which is O(k/epsilon^2) and the lower bound which is $Omega(k/epsilon^2 log(1/epsilon)). The main technical tool we use is bias amplification with the s-wide replacement product. The sum of two independent samples from a biased set is epsilon^2 biased. Rozenman and Wigderson showed how to amplify the bias more economically by choosing two samples with an expander. Based on that they suggested a recursive construction that achieves sample size O(k/epsilon^4). We show that amplification with a long random walk over the s-wide replacement product reduces the bias almost optimally.

Foundations of Computer Science Seminar

Date:
25
Thursday
May
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Locally testable and locally correctable codes approaching the Gilbert-Varshamov bound
Location: Elaine and Bram Goldsmith Building for Mathematics and Computer Sciences
Lecturer: Swastik Kopparty
Organizer: Faculty of Mathematics and Computer Science
Abstract: We show that there exist binary locally testable codes (for all rates) and local ...We show that there exist binary locally testable codes (for all rates) and locally correctable codes (for low rates) with rate and distance approaching the Gilbert-Varshamov bound (which is the best rate-distance tradeoff known for general binary error-correcting codes). Our constructions use a number of ingredients: Thommesen's random concatenation technique, the Guruswami-Sudan-Indyk strategy for list-decoding concatenated codes, the Alon-Edmonds-Luby distance amplification method, and the local list-decodability and local testability of Reed-Muller codes. Interestingly, this seems to be the first time that local testability is used in the construction of locally correctable codes. Joint work with Sivakanth Gopi, Rafael Oliveira, Noga Ron-Zewi and Shubhangi Saraf

Vision and Robotics Seminar

Date:
25
Thursday
May
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Neuronal "Ignitions" underlying stable representations in a dynamic visual environment
Location: Jacob Ziskind Building
Lecturer: Rafi Malach
Organizer: Faculty of Mathematics and Computer Science
Abstract: The external world is in a constant state of flow- posing a major challenge to n ...The external world is in a constant state of flow- posing a major challenge to neuronal representations of the visual system that necessitate sufficient time for integration and perceptual decisions. In my talk I will discuss the hypothesis that one solution to this challenge is implemented by breaking the neuronal responses into a series of discrete and stable states. I will propose that these stable points are likely implemented through relatively long lasting "ignitions" of recurrent neuronal activity. Such ignitions are a pre-requisite for the emergence of a perceptual image in the mind of the observer. The self-sustained nature of the ignitions endows them with stability despite the dynamically changing inputs. Results from intracranial recordings in patients conducted for clinical diagnostic purposes during rapid stimulus presentations, ecological settings, blinks and saccadic eye movements will be presented in support of this hypothesis.

Algebraic Geometry and Representation Theory Seminar

Date:
23
Tuesday
May
2017
Lecture / Seminar
Time: 11:15-12:30
Title: On the depth r Bernstein projector.
Location: Jacob Ziskind Building
Lecturer: Yakov Varshavsky
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
18
Thursday
May
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Regularization by Denoising (RED)
Location: Jacob Ziskind Building
Lecturer: Michael Elad
Organizer: Faculty of Mathematics and Computer Science
Abstract: Image denoising is the most fundamental problem in image enhancement, and it is ...Image denoising is the most fundamental problem in image enhancement, and it is largely solved: It has reached impressive heights in performance and quality -- almost as good as it can ever get. But interestingly, it turns out that we can solve many other problems using the image denoising "engine". I will describe the Regularization by Denoising (RED) framework: using the denoising engine in defining the regularization of any inverse problem. The idea is to define an explicit image-adaptive regularization functional directly using a high performance denoiser. Surprisingly, the resulting regularizer is guaranteed to be convex, and the overall objective functional is explicit, clear and well-defined. With complete flexibility to choose the iterative optimization procedure for minimizing this functional, RED is capable of incorporating any image denoising algorithm as a regularizer, treat general inverse problems very effectively, and is guaranteed to converge to the globally optimal result. * Joint work with Peyman Milanfar (Google Research) and Yaniv Romano (EE-Technion).

Machine Learning and Statistics Seminar

Date:
17
Wednesday
May
2017
Lecture / Seminar
Time: 11:15-12:15
Title: Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path
Location: Jacob Ziskind Building
Lecturer: Aryeh Kontorovich
Organizer: Faculty of Mathematics and Computer Science
Abstract: We propose a procedure (the first of its kind) for computing a fully data-depend ...We propose a procedure (the first of its kind) for computing a fully data-dependent interval that traps the mixing time t_mix of a finite reversible ergodic Markov chain at a prescribed confidence level. The interval is computed from a single finite-length sample path from the Markov chain, and does not require the knowledge of any parameters of the chain. This stands in contrast to previous approaches, which either only provide point estimates, or require a reset mechanism, or additional prior knowledge. The interval is constructed around the relaxation time t_relax, which is strongly related to the mixing time, and the width of the interval converges to zero roughly at a sqrt{n} rate, where n is the length of the sample path. Upper and lower bounds are given on the number of samples required to achieve constant-factor multiplicative accuracy. The lower bounds indicate that, unless further restrictions are placed on the chain, no procedure can achieve this accuracy level before seeing each state at least Omega(t_relax) times on the average. Future directions of research are identified. Time permitting, we will mention some recent further developments by D. Levin and Y. Peres. Join work with Daniel Hsu and Csaba Szepesvári

Foundations of Computer Science Seminar

Date:
15
Monday
May
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Monitoring Properties of Large, Distributed, Dynamic Graphs
Location: Jacob Ziskind Building
Lecturer: Daniel Keren
Organizer: Faculty of Mathematics and Computer Science
Abstract: Graphs that are prevalent in current applications (the Internet, Facebook etc.) ...Graphs that are prevalent in current applications (the Internet, Facebook etc.) are not only very large and highly dynamic, but also distributed between many servers, none of which sees the graph in its entirety. The distributed monitoring problem deals with the question of imposing conditions on the local graphs, such that as long as they hold, it is guaranteed that some desired property holds for the global graph. While defining local conditions for linear properties (e.g. average degree) is relatively easy, they are more difficult to derive for non-linear functions over the graph. We propose a solution and a general definition of solution optimality, and demonstrate how to apply it to two important graph properties -- spectral gap and number of triangles. We also define an absolute lower bound on the communication overhead for distributed monitoring, and compare our algorithm to it, with good results. Performance improves as the graph becomes larger and denser -- that is, when distributing it is more important.

Foundations of Computer Science Seminar

Date:
08
Monday
May
2017
Lecture / Seminar
Time: 14:30-16:00
Title: From Ants to Query Complexity
Location: Jacob Ziskind Building
Lecturer: Amos Korman
Organizer: Faculty of Mathematics and Computer Science
Abstract: I will talk about my recent adventures with ants. Together with biologists we st ...I will talk about my recent adventures with ants. Together with biologists we study P. longicornis ants as they collaboratively transport a large food item to their nest. This collective navigation process is guided by pheromones which are laid by individual ants. Using a new methodology to detect scent marks, we identify a new kind of ant trail characterized by very short and dynamic pheromone markings and highly stochastic navigation response to them. We argue that such a trail can be highly beneficial in conditions in which knowledge of individual ants regarding the underlying topological structure is unreliable. This gives rise to a new theoretical search model on graphs under unreliable guiding instructions, which is of independent computational interest. To illustrate the model, imagine driving a car in an unknown country that is in the aftermath of a major hurricane which has randomly flipped a certain small fraction of the road-signs. Under such conditions of unreliability, how can you still reach your destination fast? I will discuss the limits of unreliability that allow for efficient navigation. In trees, for example, there is a phase transition phenomenon that occurs roughly around the inverse of the square root of the maximal degree. That is, if noise is above this threshold then any algorithm cannot avoid finding the target in exponential time (in the original distance), while below the threshold we identify an optimal, almost linear, walking algorithm. Finally, I will discuss algorithms that under such a noisy model aim to minimize the number of queries to find a target (rather than the number of moves). This talk is based on joint works with biologists from the Weizmann Institute: Ofer Feinerman, Udi Fonio, and others, and with CS researchers: Lucas Bockowski, Adrian Kosowski, and Yoav Rodeh.

Example 2 for internal event node

Date:
08
Monday
May
2017
-
10
Wednesday
May
2017
Retreat
Time: 10:00 - 12:30
Location: David Lopatie Conference Centre ...
Organizer: Department of ...

Example 1 for internal event node

Date:
08
Monday
May
2017
-
10
Wednesday
May
2017
Retreat
Time: 10:00 - 12:30
Location: David Lopatie Conference Centre ...
Organizer: Department of ...

Vision and Robotics Seminar

Date:
27
Thursday
April
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Motion compositionality and timing: combined geometrical and optimization approaches
Location: Jacob Ziskind Building
Lecturer: Tamar Flash
Organizer: Faculty of Mathematics and Computer Science
Abstract: In my talk I will discuss several recent research directions that we have taken ...In my talk I will discuss several recent research directions that we have taken to explore the different principles underlying the construction and control of complex human upper arm and gait movements. One important topic is motor compositionality, exploring the nature of the motor primitives underlying the construction of complex movements at different levels of the motor hierarchy. The second topic which we focused on is motion timing, investigating what principles dictate the durations of complex sequential behaviors both at the level of the internal timing of different motion segments and the total durations of different types of movement. Finally I will discuss the topic of motor coordination and the mapping between end-effector and joint motions both during arm and leg movements using various dimension reduction approaches. The mathematical models we have used to study the above topics combine geometrical approaches with optimization models to derive motion invariants, optimal control principles and different conservations laws.

Algebraic Geometry and Representation Theory Seminar

Date:
25
Tuesday
April
2017
Lecture / Seminar
Time: 11:15-12:30
Title: A new category of sl(infinity)-modules related to Lie superalgebras
Location: Elaine and Bram Goldsmith Building for Mathematics and Computer Sciences
Lecturer: Crystal Hoyt
Organizer: Faculty of Mathematics and Computer Science
Abstract: The (reduced) Grothendieck group of the category of finite-dimensional represent ...The (reduced) Grothendieck group of the category of finite-dimensional representations of the Lie superalgebra gl(m|n) is an sl(infinity)-module with the action defined via translation functors, as shown by Brundan and Stroppel. This module is indecomposable and integrable, but does not lie in the tensor category, in other words, it is not a subquotient of the tensor algebra generated by finitely many copies of the natural and conatural sl(infinity)-modules. In this talk, we will introduce a new category of sl(infinity)-modules in which this module is injective, and describe the socle filtration of this module. Joint with: I. Penkov, V. Serganova

Foundations of Computer Science Seminar

Date:
24
Monday
April
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Some simple distributed network processes
Location: Jacob Ziskind Building
Lecturer: Luca Trevisan
Organizer: Faculty of Mathematics and Computer Science
Abstract: We will describe network processes in which, at each step, each node communicate ...We will describe network processes in which, at each step, each node communicates with its neighbors, or a random subset of neighbors, and it updates its state to be "more like" the state of the neighbors. In a discrete setting, where there is a finite set of possible states, each node node updates to the state held by a plurality of sampled neighbors. Here we show that, in a complete communication network, there is a quick convergence to a consensus, regardless of the initial configuration and even in the presence of adversarial faults. If the set of possible states is ordered, and nodes update to the median of neighbors, convergence was known to be even faster, but less robust to adversarial tampering. In a continuous setting, each node holds a bounded real number, and it updates to the average of sampled neighbors. Here we show that if the graph has a clustered structure, such as the one generated by the stochastic block model, the nodes can identify the cluster they belong to based on the evolution of the local state. This holds even in an asynchronous model in which only two nodes are active at a time, and the study of the latter setting leads to interesting questions about the concentration of the product of iid random matrices. (Based on joint work with Luca Becchetti, Andrea Clementi, Pasin Manurangsi, Emanuele Natale, Francesco Pasquale and Prasad Raghavendra.)

Vision and Robotics Seminar

Date:
20
Thursday
April
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Separating the Wheat from the Chaff in Visual Data
Location: Jacob Ziskind Building
Lecturer: Lihi Zelnik-Manor
Organizer: Faculty of Mathematics and Computer Science
Abstract: By far, most of the bits in the world are image and video data. YouTube alone ge ...By far, most of the bits in the world are image and video data. YouTube alone gets 300 hours of video uploaded every minute. Adding to that personal pictures, videos, TV channels and the gazillion of security cameras shooting 24/7 one quickly sees that the amount of visual data being recorded is colossal. In the first part of this talk I will discuss the problem of "saliency prediction" - separating between the important parts of images/videos (the "wheat") from the less important ones (the "chaff"). I will review work done over the last decade and its achievements. In the second part of the talk I will discuss one particular application of saliency prediction that our lab is interested in: making images and videos accessible to the visually impaired. Our plan is to convert images and videos into tactile surfaces that can be "viewed" by touch. As it turns out, saliency estimation and manipulation both play a key factor in this task.

Machine Learning and Statistics Seminar

Date:
19
Wednesday
April
2017
Lecture / Seminar
Time: 11:15-12:30
Title: A Deeper Understanding of Deep Learning
Location: Jacob Ziskind Building
Lecturer: Naftali Tishby
Organizer: Faculty of Mathematics and Computer Science
Abstract: By analytical and numerical studies of Deep Neural Networks (using standard Tens ...By analytical and numerical studies of Deep Neural Networks (using standard TensorFlow) in the "Information Plane" - the Mutual Information the network layers preserve on the input and the output variables - we obtain the following new insights. 1: The training epochs, for each layer, are divided into two phases: (1) fitting the training data - increasing the mutual information on the labels

Algebraic Geometry and Representation Theory Seminar

Date:
18
Tuesday
April
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Coadjoint orbits, Kostant–Kumar polynomials and tangent cones to Schubert varieties
Location: Elaine and Bram Goldsmith Building for Mathematics and Computer Sciences
Lecturer: Mikhail Ignatyev
Organizer: Faculty of Mathematics and Computer Science
Abstract: TBA ...TBA

Vision and Robotics Seminar

Date:
06
Thursday
April
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Occlusion-Aware Template Matching via Consensus Set Maximization
Location: Jacob Ziskind Building
Lecturer: Simon Korman
Organizer: Faculty of Mathematics and Computer Science
Abstract: We present a novel approach to template matching that is efficient, can handle p ...We present a novel approach to template matching that is efficient, can handle partial occlusions, and is equipped with provable performance guarantees. A key component of the method is a reduction that transforms the problem of searching a nearest neighbor among N high-dimensional vectors, to searching neighbors among two sets of order sqrt(N) vectors, which can be done efficiently using range search techniques. This allows for a quadratic improvement in search complexity, that makes the method scalable when large search spaces are involved. For handling partial occlusions, we develop a hashing scheme based on consensus set maximization within the range search component. The resulting scheme can be seen as a randomized hypothesize-and-test algorithm, that comes with guarantees regarding the number of iterations required for obtaining an optimal solution with high probability. The predicted matching rates are validated empirically and the proposed algorithm shows a significant improvement over the state-of-the-art in both speed and robustness to occlusions. Joint work with Stefano Soatto.

Foundations of Computer Science Seminar

Date:
03
Monday
April
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Circuit based PSI via Cuckoo Hashing
Location: Jacob Ziskind Building
Lecturer: Udi Wieder
Organizer: Faculty of Mathematics and Computer Science
Abstract: While there has been a lot of progress in designing efficient custom protocols f ...While there has been a lot of progress in designing efficient custom protocols for computing Private Set Intersection (PSI), there has been less research on using generic MPC protocols for this task. However, there are many variants of the set intersection functionality which seem hard to compute with existing custom protocols and are easy to compute with generic MPC based solutions (for example comparing the cardinality of the intersection with a threshold or measuring ad conversion rates). Generic protocols work over circuits which compute the intersection. For sets of size n the best known circuit constructions compute O(n log n) comparisons. In this work we propose new circuit-based protocols for computing variants of the intersection, with circuits computing only O(n) comparisons. Our constructions are based on a new variant of Cuckoo hashing in two dimensions. We employ several optimizations and determine experimentally the required sizes of tables and circuits, and measure the runtime, showing that our protocol is more efficient in concrete terms than existing constructions. The proof technique is new and can be generalized to analyzing simple Cuckoo hashing as well as new variants.

Vision and Robotics Seminar

Date:
30
Thursday
March
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Unsupervised Cross-Domain Image Generation
Location: Jacob Ziskind Building
Lecturer: Lior Wolf
Organizer: Faculty of Mathematics and Computer Science
Abstract: We study the ecological use of analogies in AI. Specifically, we address the pro ...We study the ecological use of analogies in AI. Specifically, we address the problem of transferring a sample in one domain to an analog sample in another domain. Given two related domains, S and T, we would like to learn a generative function G that maps an input sample from S to the domain T, such that the output of a given representation function f, which accepts inputs in either domains, would remain unchanged. Other than f, the training data is unsupervised and consist of a set of samples from each domain, without any mapping between them. The Domain Transfer Network (DTN) we present employs a compound loss function that includes a multiclass GAN loss, an f preserving component, and a regularizing component that encourages G to map samples from T to themselves. We apply our method to visual domains including digits and face images and demonstrate its ability to generate convincing novel images of previously unseen entities, while preserving their identity. Joint work with Yaniv Taigman and Adam Polyak

Foundations of Computer Science Seminar

Date:
27
Monday
March
2017
Lecture / Seminar
Time: 14:30-16:00
Title: On polynomial approximations to AC0
Location: Jacob Ziskind Building
Lecturer: Prahladh Harsha
Organizer: Faculty of Mathematics and Computer Science
Abstract: In this talk, we will discuss some questions related to polynomial approximation ...In this talk, we will discuss some questions related to polynomial approximations of AC0. A classic result due to Tarui (1991) and Beigel, Reingold, and Spielman (1991), states that any AC0 circuit of size s and depth d has an ε-error probabilistic polynomial over the reals of degree at most (log(s/ε))^O(d). We will have a re-look at this construction and show how to improve the bound to (log s)^{O(d)}⋅log(1/ε), which is much better for small values of ε. As an application of this result, we show that (log s)^{O(d)}⋅log(1/ε)-wise independence fools AC0, improving on Tal's strengthening of Braverman's theorem that (log(s/ε))^{O(d)}-wise independence fools AC0. Time permitting, we will also discuss some lower bounds on the best polynomial approximations to AC0. Joint work with Srikanth Srinivasan

Mathematical Analysis and Applications Seminar

Date:
07
Tuesday
March
2017
Lecture / Seminar
Time: 11:15-13:00
Title: Local density of states and the spectral function for almost-periodic operators.
Location: Jacob Ziskind Building
Lecturer: Leonid Parnovski
Organizer: Faculty of Mathematics and Computer Science
Abstract: I will discuss the asymptotic behaviour (both on and off the diagonal) of the sp ...I will discuss the asymptotic behaviour (both on and off the diagonal) of the spectral function of a Schroedinger operator with smooth bounded potential when energy becomes large. I formulate the conjecture that the local density of states (i.e. the spectral function on the diagonal) admits the complete asymptotic expansion and discuss the known results, mostly for almost-periodic potentials.

Geometric Functional Analysis and Probability Seminar

Date:
23
Thursday
February
2017
Lecture / Seminar
Time: 11:15-13:00
Title: Conditional determinantal processes are determinantal
Location: Jacob Ziskind Building
Lecturer: Sasha Shamov
Organizer: Faculty of Mathematics and Computer Science
Abstract: A determinantal point process governed by a locally trace class Hermitian contra ...A determinantal point process governed by a locally trace class Hermitian contraction kernel on a measure space $E$ remains determinantal when conditioned on its configuration on an arbitrary measurable subset $B subset E$. Moreover, the conditional kernel can be chosen canonically in a way that is "local" in a non-commutative sense, i.e. invariant under "restriction" to closed subspaces $L^2(B) subset P subset L^2(E)$. Using the properties of the canonical conditional kernel we establish a conjecture of Lyons and Peres: if $K$ is a projection then almost surely all functions in its image can be recovered by sampling at the points of the process.

Algebraic Geometry and Representation Theory Seminar

Date:
21
Tuesday
February
2017
Lecture / Seminar
Time: 11:15-13:00
Title: A conjectured cohomological description of special values of zeta-functions.
Location: Jacob Ziskind Building
Lecturer: Stephen Lichtenbaum
Organizer: Faculty of Mathematics and Computer Science
Abstract: Let X be a regular scheme, projective and flat over Spec Z. We give a conjectur ...Let X be a regular scheme, projective and flat over Spec Z. We give a conjectural formula in terms of motivic cohomology, singular cohomology and de Rham cohomology for the special value of the zeta-function of X at any rational integer. We will explain how this reduces to the standard formula for the residue of the Dedekind zeta-function at s = 1.

Mathematical Analysis and Applications Seminar

Date:
14
Tuesday
February
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Averaging over a non-ergodic system
Location: Jacob Ziskind Building
Lecturer: Dimitry Turaev
Organizer: Faculty of Mathematics and Computer Science
Abstract: A classical theorem by Anosov states that the slow motion of a slow-fast system ...A classical theorem by Anosov states that the slow motion of a slow-fast system where the fast subsystem is ergodic with respect to a smooth invariant measure can be approximated, in a well-defined sense, by the slow subsystem averaged over the fast variables. We address the question of what happens if the fast system is not ergodic. We discuss a theory which is developing in joint works with V. Gelfreich, T. Pereira, V. Rom-Kedar and K. Shah, and suggest that in the non-ergodic case the behavior of the slow variables is approximated by a random process, and not a single, deterministic averaged system. We also discuss the question of the relevance of ergodicity to the foundations of statistical mechanics.

Seminar in Geometry and Topology

Date:
13
Monday
February
2017
Lecture / Seminar
Time: 16:15-17:45
Title: Eigenvalue bounds on surfaces: some recent advances
Location: Jacob Ziskind Building
Lecturer: Mikhail Karpukhin
Organizer: Faculty of Mathematics and Computer Science
Abstract: We will give an overview of some recent results on Laplace and Steklov eigenvalu ...We will give an overview of some recent results on Laplace and Steklov eigenvalue estimates on Riemannian surfaces. In particular, we will present an upper bound on the first Laplace eigenvalue for non-orientable surfaces, extending some classical inequalities due to Yang, Li and Yau. We will also discuss the Steklov eigenvalue problem that has attracted a lot of attention in the past decade. In particular, geometric estimates on Steklov eigenvalues of arbitrary index will be presented.

Vision and Robotics Seminar

Date:
09
Thursday
February
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Deformation-aware image processing
Location: Jacob Ziskind Building
Lecturer: Tomer Michaeli
Organizer: Faculty of Mathematics and Computer Science
Abstract: Image processing algorithms often involve a data fidelity penalty, which encoura ...Image processing algorithms often involve a data fidelity penalty, which encourages the solution to comply with the input data. Existing fidelity measures (including perceptual ones) are very sensitive to slight misalignments in the locations and shapes of objects. This is in sharp contrast to the human visual system, which is typically indifferent to such variations. In this work, we propose a new error measure, which is insensitive to small smooth deformations and is very simple to incorporate into existing algorithms. We demonstrate our approach in lossy image compression. As we show, optimal encoding under our criterion boils down to determining how to best deform the input image so as to make it “more compressible”. Surprisingly, it turns out that very minor deformations (almost imperceptible in some cases) suffice to make a huge visual difference in methods like JPEG and JPEG2000. Thus, by slightly sacrificing geometric integrity, we gain a significant improvement in preservation of visual information. We also show how our approach can be used to visualize image priors. This is done by determining how images should be deformed so as to best conform to any given image model. By doing so, we highlight the elementary geometric structures to which the prior resonates. Using this method, we reveal interesting behaviors of popular priors, which were not noticed in the past. Finally, we illustrate how deforming images to possess desired properties can be used for image `idealization’ and for detecting deviations from perfect regularity. Joint work with Tamar Rott Shaham, Tali Dekel, Michal Irani, and Bill Freeman.

Geometric Functional Analysis and Probability Seminar

Date:
09
Thursday
February
2017
Lecture / Seminar
Time: 11:15
Title: The values of quadratic forms on difference sets, measure rigidity and equidistribution
Location: Jacob Ziskind Building
Lecturer: Alexander Fish
Organizer: Faculty of Mathematics and Computer Science

Geometric Functional Analysis and Probability Seminar

Date:
09
Thursday
February
2017
Lecture / Seminar
Time: 11:15-13:00
Title: The values of quadratic forms on difference sets, measure rigidity and equidistribution
Location: Jacob Ziskind Building
Lecturer: Alexander Fish
Organizer: Faculty of Mathematics and Computer Science

Machine Learning and Statistics Seminar

Date:
08
Wednesday
February
2017
Lecture / Seminar
Time: 11:15-12:15
Title: Large-scale and Non-approximate Kernel Methods Using Random Features
Location: Jacob Ziskind Building
Lecturer: Haim Avron
Organizer: Faculty of Mathematics and Computer Science
Abstract: Kernel methods constitute a mathematically elegant framework for general-purpose ...Kernel methods constitute a mathematically elegant framework for general-purpose infinite-dimensional non-parametric statistical inference. By providing a principled framework to extend classical linear statistical techniques to non-parametric modeling, their applications span the entire spectrum of statistical learning. However, training procedures naturally derived via this framework scale poorly and with limited opportunities for parallelization. This poor scalability poses a significant barrier for the use of kernel methods in big data applications. As such, with the growth in data across a multitude of applications, scaling up kernel methods has acquired renewed and somewhat urgent significance. Random feature maps, such as random Fourier features, have recently emerged as a powerful technique for speeding up and scaling the training of kernel-based methods. However, random feature maps only provide crude approximations to the kernel function, so delivering state-of-the-art results requires huge amount of random features. Nevertheless, in some cases, even when the number of random features is driven to be as large as the training size, full recovery of the generalization performance of the exact kernel method is not attained. In the talk I will show how random feature maps can be used to efficiently perform non-approximate kernel ridge regression, and thus there is no need to compromise between quality and running time. The core idea is to use random feature maps to form preconditioners to be used in solving kernel ridge regression to high accuracy. I will describe theoretical conditions on when this yields an effective preconditioner, and empirically evaluate the method and show it is highly effective for datasets of up to one million training examples.

Machine Learning and Statistics Seminar

Date:
08
Wednesday
February
2017
Lecture / Seminar
Time: 11:15-12:15
Title: Large-scale and Non-approximate Kernel Methods Using Random Features
Location: Jacob Ziskind Building
Lecturer: Haim Avron
Organizer: Faculty of Mathematics and Computer Science
Abstract: Kernel methods constitute a mathematically elegant framework for general-purpose ...Kernel methods constitute a mathematically elegant framework for general-purpose infinite-dimensional non-parametric statistical inference. By providing a principled framework to extend classical linear statistical techniques to non-parametric modeling, their applications span the entire spectrum of statistical learning. However, training procedures naturally derived via this framework scale poorly and with limited opportunities for parallelization. This poor scalability poses a significant barrier for the use of kernel methods in big data applications. As such, with the growth in data across a multitude of applications, scaling up kernel methods has acquired renewed and somewhat urgent significance. Random feature maps, such as random Fourier features, have recently emerged as a powerful technique for speeding up and scaling the training of kernel-based methods. However, random feature maps only provide crude approximations to the kernel function, so delivering state-of-the-art results requires huge amount of random features. Nevertheless, in some cases, even when the number of random features is driven to be as large as the training size, full recovery of the generalization performance of the exact kernel method is not attained. In the talk I will show how random feature maps can be used to efficiently perform non-approximate kernel ridge regression, and thus there is no need to compromise between quality and running time. The core idea is to use random feature maps to form preconditioners to be used in solving kernel ridge regression to high accuracy. I will describe theoretical conditions on when this yields an effective preconditioner, and empirically evaluate the method and show it is highly effective for datasets of up to one million training examples.

Foundations of Computer Science Seminar

Date:
06
Monday
February
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Efficient Empirical Revenue Maximization in Single-Parameter Auction Environments
Location: Jacob Ziskind Building
Lecturer: Yannai A. Gonczarowski
Organizer: Faculty of Mathematics and Computer Science
Abstract: We present a polynomial-time algorithm that, given samples from the unknown valu ...We present a polynomial-time algorithm that, given samples from the unknown valuation distribution of each bidder, learns an auction that approximately maximizes the auctioneer's revenue in a variety of single-parameter auction environments including matroid environments, position environments, and the public project environment. The valuation distributions may be arbitrary bounded distributions (in particular, they may be irregular, and may differ for the various bidders), thus resolving a problem left open by previous papers. The analysis uses basic tools, is performed in its entirety in value-space, and simplifies the analysis of previously known results for special cases. Furthermore, the analysis extends to certain single-parameter auction environments where precise revenue maximization is known to be intractable, such as knapsack environments. Joint work with Noam Nisan.

Algebraic Geometry and Representation Theory Seminar

Date:
03
Friday
February
2017
Lecture / Seminar
Time: 10:30-12:00
Title: Fourier transformation and hyperplane arrangements
Location: Jacob Ziskind Building
Lecturer: Vadim Schechtman
Organizer: Faculty of Mathematics and Computer Science
Abstract: Linear algebra problems related to the Fourier transformation of perverse sheave ...Linear algebra problems related to the Fourier transformation of perverse sheaves smooth along a hyperplane arrangement in an affine space, together with some examples coming from the representation theory will be discussed.

Machine Learning and Statistics Seminar

Date:
01
Wednesday
February
2017
Lecture / Seminar
Time: 11:15-12:15
Title: CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy
Location: Jacob Ziskind Building
Lecturer: Ran Gilad-Bachrach
Organizer: Faculty of Mathematics and Computer Science
Abstract: Applying machine learning to a problem which involves medical, financial, or oth ...Applying machine learning to a problem which involves medical, financial, or other types of sensitive data, not only requires accurate predictions but also careful attention to maintaining data privacy and security. Legal and ethical requirements may prevent the use of cloud-based machine learning solutions for such tasks. In this work, we will present a method to convert learned neural networks to CryptoNets, neural networks that can be applied to encrypted data. This allows a data owner to send their data in an encrypted form to a cloud service that hosts the network. The encryption ensures that the data remains confidential since the cloud does not have access to the keys needed to decrypt it. Nevertheless, we will show that the cloud service is capable of applying the neural network to the encrypted data to make encrypted predictions, and also return them in encrypted form. These encrypted predictions can be sent back to the owner of the secret key who can decrypt them. Therefore, the cloud service does not gain any information about the raw data nor about the prediction it made. We demonstrate CryptoNets on the MNIST optical character recognition tasks. CryptoNets achieve 99% accuracy and can make around 59000 predictions per hour on a single PC. Therefore, they allow high throughput, accurate, and private predictions. This is a joint work with Nathan Dowlin, Kim Laine, Kristin Lauter, Michael Naehrig, John Wernsing.

Algebraic Geometry and Representation Theory Seminar

Date:
31
Tuesday
January
2017
Lecture / Seminar
Time: 11:15-12:30
Title: What do algebras form? (Revisited)
Location: Jacob Ziskind Building
Lecturer: Boris Tsygan
Organizer: Faculty of Mathematics and Computer Science
Abstract: We will start with the observation that assocciative algebras form a two-categor ...We will start with the observation that assocciative algebras form a two-category with a trace functor where one-morphisms are bimodules, two-morphisms are bimodule homomorphisms, and the trace of an (A,A) bimodule M is M/[M,A]. We then explain in what sense the derived version of the above is true, I.e. what happens when one replaces bimodule homomorrphisms and the trace by their derived functors that are Hochschild (com)homology. We will explain how the beginnings of noncommutative differential calculus can bee deduced from the above. This is a continuation of a series of works of MacClure and Smith, Tamarkin, Lurie, and others, and a joint work with Rebecca Wei.

Mathematical Analysis and Applications Seminar

Date:
31
Tuesday
January
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Sloshing, Steklov and corners
Location: Jacob Ziskind Building
Lecturer: Iosif Polterovich
Organizer: Faculty of Mathematics and Computer Science
Abstract: The sloshing problem is a Steklov type eigenvalue problem describing small oscil ...The sloshing problem is a Steklov type eigenvalue problem describing small oscillations of an ideal fluid. We will give an overview of some latest advances in the study of Steklov and sloshing spectral asymptotics, highlighting the effects arising from corners, which appear naturally in the context of sloshing. In particular, we will outline an approach towards proving the conjectures posed by Fox and Kuttler back in 1983 on the asymptotics of sloshing frequencies in two dimensions. The talk is based on a joint work in progress with M. Levitin, L. Parnovski and D. Sher.

Foundations of Computer Science Seminar

Date:
30
Monday
January
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Graph Isomorphism in quasipolynomial time
Location: Jacob Ziskind Building
Lecturer: Laszlo Babai
Organizer: Faculty of Mathematics and Computer Science

The Chaim Leib Pekeris Memorial Lecture

Date:
29
Sunday
January
2017
Lecture / Seminar
Time: 11:00-12:30
Title: Hidden irregularity versus hidden symmetry
Lecturer: Laszlo Babai
Organizer: Faculty of Mathematics and Computer Science
Abstract: Symmetry is defined in terms of structure-preserving transformations (automorph ...Symmetry is defined in terms of structure-preserving transformations (automorphisms); regularity in terms of numerical invariants. Symmetry always implies regularity but there are many highly regular combinatorial objects (such as ``strongly regular graphs'') with no symmetry. The opposite of irregularity is regularity, not symmetry. Yet we show that in a well-defined sense, emph{the opposite of hidden irregularity is hidden symmetry,} and in fact hidden symmetry of a particularly robust kind. The symmetry of a circle is easily destroyed: just ``individualize'' two non-opposite points -- color one of them red, the other blue -- and all the symmetry is gone. In fact, the resulting structure is completely irregular: every point is uniquely identified by a pair of numerical invariants, namely, its pair of distances to the two individualized points. We shall say that the circle has a high degree of hidden irregularity. In contrast, emph{Johnson graphs} are objects with robust symmetry: individualizing a small number of vertices of a Johnson graph hardly makes a dent in its symmetry. Recent work on the algorithmic problem of Graph Isomorphism has revealed that Johnson graphs are unique in this regard: Every finite relational structure of small arity either has a measurable (say 10\%) hidden irregularity (revealed by individualizing a polylogarithmic number of elements) or has a large degree of hidden symmetry, manifested in a canonically embedded Johnson graph on more than 90\% of the underlying set. This dichotomy is the key Divide-and-Conquer tool in recent progress on the worst-case complexity of the Graph Isomorphism problem. This subject is purely combinatorial and does not require advanced mathematical apparatus. The group theoretic aspects of the new Graph Isomorphism test will be discussed in a follow-up seminar on January 30.

Vision and Robotics Seminar

Date:
26
Thursday
January
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Signal Modeling: From Convolutional Sparse Coding to Convolutional Neural Networks
Location: Jacob Ziskind Building
Lecturer: Vardan Papyan
Organizer: Faculty of Mathematics and Computer Science

Machine Learning and Statistics Seminar

Date:
25
Wednesday
January
2017
Lecture / Seminar
Time: 11:15-12:15
Title: Variational Conditional Probabilities
Location: Jacob Ziskind Building
Lecturer: Amir Globerson
Organizer: Faculty of Mathematics and Computer Science
Abstract: Predicting the label Y of an object X is a core task in machine learning. From a ...Predicting the label Y of an object X is a core task in machine learning. From a probabilistic perspective, this involves reasoning about conditional probabilities p(y|x). However, it is hard to obtain reliable estimates for these probabilities. Here we show how to obtain lower and upper bounds on p(y|x) given statistical information, and show how it can be used within various learning setups. We also extend this formulation to the structured case, where y can be multivariate.

Algebraic Geometry and Representation Theory Seminar

Date:
24
Tuesday
January
2017
Lecture / Seminar
Time: 11:15-12:30
Title: “Size" of a representation of a finite group controls the size of its character values
Location: Jacob Ziskind Building
Lecturer: Shamgar Gurevich
Organizer: Faculty of Mathematics and Computer Science

Guest Seminar

Date:
24
Tuesday
January
2017
Lecture / Seminar
Time: 10:00-12:00
Title: Detecting human genetic adaptation in historical timescales
Location: Elaine and Bram Goldsmith Building for Mathematics and Computer Sciences
Lecturer: Yair Field
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
23
Monday
January
2017
Lecture / Seminar
Time: 14:30-16:00
Title: The FedEx Problem
Location: Jacob Ziskind Building
Lecturer: Kira Goldner
Organizer: Faculty of Mathematics and Computer Science
Abstract: Consider the following setting: a customer has a package and is willing to pay u ...Consider the following setting: a customer has a package and is willing to pay up to some value v to ship it, but needs it to be shipped by some deadline d. Given the joint prior distribution from which (v, d) pairs are drawn, we characterize the auction that yields optimal revenue, contributing to the very limited understanding of optimal auctions beyond the single-parameter setting. Our work further demonstrates the importance of 'ironing' in revenue maximization, helping to illustrate why randomization is necessary to achieve optimal revenue. Finally, we strengthen the emerging understanding that duality is useful for both the design and analysis of optimal auctions in multi- parameter settings. Joint work with Amos Fiat, Anna Karlin, and Elias Koutsoupias.

Foundations of Computer Science Seminar

Date:
22
Sunday
January
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Graph Algorithms for Distributed Networks
Location: Jacob Ziskind Building
Lecturer: Merav Parter
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
19
Thursday
January
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Robots in Clutter: Learning to Understand Environmental Changes
Location: Jacob Ziskind Building
Lecturer: David Held
Organizer: Faculty of Mathematics and Computer Science
Abstract: Robots today are confined to operate in relatively simple, controlled environmen ...Robots today are confined to operate in relatively simple, controlled environments. One reason for this is that current methods for processing visual data tend to break down when faced with occlusions, viewpoint changes, poor lighting, and other challenging but common situations that occur when robots are placed in the real world. I will show that we can train robots to handle these variations by modeling the causes behind visual appearance changes. If robots can learn how the world changes over time, they can be robust to the types of changes that objects often undergo. I demonstrate this idea in the context of autonomous driving, and I will show how we can use this idea to improve performance for every step of the robotic perception pipeline: object segmentation, tracking, velocity estimation, and classification. I will also present some preliminary work on learning to manipulate objects, using a similar framework of learning environmental changes. By learning how the environment can change over time, we can enable robots to operate in the complex, cluttered environments of our daily lives.

Geometric Functional Analysis and Probability Seminar

Date:
19
Thursday
January
2017
Lecture / Seminar
Time: 11:15-13:00
Title: Tightness for the Cover Time of S^2
Location: Jacob Ziskind Building
Lecturer: Jay Rosen
Organizer: Faculty of Mathematics and Computer Science

Mathematical Analysis and Applications Seminar

Date:
17
Tuesday
January
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Minimal representatives and the Lorenz equations
Location: Jacob Ziskind Building
Lecturer: Tali Pinsky
Organizer: Faculty of Mathematics and Computer Science
Abstract: A minimal representative for a dynamical system is a system that has the simples ...A minimal representative for a dynamical system is a system that has the simplest possible dynamics in its topological equivalence class. This is very much related to "dynamical forcing": when existence of certain periodic orbits forces existence of others. This is quite useful in the analysis of chaotic systems. I'll give examples of minimal representatives in dimensions one, two and three. In dimension three, I'll show that the minimal representative for the chaotic Lorenz equations (for the correct parameters) is the geodesic flow on the modular surface. This will be an introductory talk.

Geometric Functional Analysis and Probability Seminar

Date:
12
Thursday
January
2017
Lecture / Seminar
Time: 11:00-13:00
Title: Double lecture !
Location: Jacob Ziskind Building
Lecturer: Ran Tessler and Assaf Naor
Organizer: Faculty of Mathematics and Computer Science

Guest Seminar

Date:
12
Thursday
January
2017
Lecture / Seminar
Time: 11:00-12:30
Title: Hardness in P
Location: Elaine and Bram Goldsmith Building for Mathematics and Computer Sciences
Lecturer: Amir Abboud
Organizer: Faculty of Mathematics and Computer Science
Abstract: The class P attempts to capture the efficiently solvable computational tasks. It ...The class P attempts to capture the efficiently solvable computational tasks. It is full of practically relevant problems, with varied and fascinating combinatorial structure. In this talk, I will give an overview of a rapidly growing body of work that seeks a better understanding of the structure within P. Inspired by NP-hardness, the main tool in this approach are combinatorial reductions. Combining these reductions with a small set of plausible conjectures, we obtain tight lower bounds on the time complexity of many of the most important problems in P.

Algebraic Geometry and Representation Theory Seminar

Date:
10
Tuesday
January
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Finite-dimensional representations of quantum affine algebras
Location: Jacob Ziskind Building
Lecturer: Jianrong Li
Organizer: Faculty of Mathematics and Computer Science
Abstract: I will talk about finite dimensional representations of quantum affine algebras. ...I will talk about finite dimensional representations of quantum affine algebras. The main topics are Chari and Pressley's classification of finite-dimensional simple modules over quantum affine algebras, Frenkel and Reshetikhin's theory of q-characters of finite dimensional modules, Frenkel-Mukhin algorithm to compute q-characters, T-systems, Hernandez-Leclerc's conjecture about the cluster algebra structure on the ring of a subcategory of the category of all finite dimensional representations of a quantum affine algebra. I will also talk about how to obtain a class of simple modules called minimal affinizations of types A, B using mutations (joint work with Bing Duan, Yanfeng Luo, Qianqian Zhang).

Seminar in Geometry and Topology

Date:
09
Monday
January
2017
Lecture / Seminar
Time: 16:15-18:00
Title: Wilkie's conjecture for restricted elementary functions
Location: Jacob Ziskind Building
Lecturer: Gal Binyamini
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
09
Monday
January
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Bipartite Perfect Matching in Pseudo-Deterministic NC
Location: Jacob Ziskind Building
Lecturer: Ofer Grossman
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
05
Thursday
January
2017
Lecture / Seminar
Time: 12:15-13:30
Title: Taking Pictures in Scattering Media
Location: Jacob Ziskind Building
Lecturer: Shai Avidan
Organizer: Faculty of Mathematics and Computer Science
Abstract: Pictures taken under bad weather conditions or underwater often suffer from low ...Pictures taken under bad weather conditions or underwater often suffer from low contrast and limited visibility. Restoring colors of images taken in such conditions is extremely important for consumer applications, computer vision tasks, and marine research. The common physical phenomena in these scenarios are scattering and absorption - the imaging is done either under water, or in a medium that contains suspended particles, e.g. dust (haze) and water droplets (fog). As a result, the colors of captured objects are attenuated, as well as veiled by light scattered by the suspended particles. The amount of attenuation and scattering depends on the objects' distance from the camera and therefore the color distortion cannot be globally corrected. We propose a new prior, termed Haze-Line, and use it to correct these types of images. First, we show how it can be used to clean images taken under bad weather conditions such as haze or fog. Then we show how to use it to automatically estimate the air light.Finally, we extend it to deal with underwater images as well. The proposed algorithm is completely automatic and quite efficient in practice. Joint work with Dana Berman (TAU) and Tali Treibitz (U.of Haifa)

Geometric Functional Analysis and Probability Seminar

Date:
05
Thursday
January
2017
Lecture / Seminar
Time: 11:00-13:00
Title: Walking within growing domains: recurrence versus transience
Location: Jacob Ziskind Building
Lecturer: Amir Dembo
Organizer: Faculty of Mathematics and Computer Science
Abstract: When is simple random walk on growing in time d-dimensional domains recurrent? F ...When is simple random walk on growing in time d-dimensional domains recurrent? For domain growth which is independent of the walk, we review recent progress and related universality conjectures about a sharp recurrence versus transience criterion in terms of the growth rate. We compare this with the question of recurrence/transience for time varying conductance models, where Gaussian heat kernel estimates and evolving sets play an important role. We also briefly contrast such expected universality with examples of the rich behavior encountered when monotone interaction enforces the growth as a result of visits by the walk to the current domain's boundary. This talk is based on joint works with Ruojun Huang, Ben Morris, Yuval Peres, Vladas Sidoravicius and Tianyi Zheng.

Machine Learning and Statistics Seminar

Date:
04
Wednesday
January
2017
Lecture / Seminar
Time: 11:15-12:30
Title: Active Nearest-Neighbor Learning in Metric Spaces
Location: Jacob Ziskind Building
Lecturer: Sivan Sabato
Organizer: Faculty of Mathematics and Computer Science
Abstract: We propose a pool-based non-parametric active learning algorithm for general met ...We propose a pool-based non-parametric active learning algorithm for general metric spaces, which outputs a nearest-neighbor classifier. We give prediction error guarantees that depend on the noisy-margin properties of the input sample, and are competitive with those obtained by previously proposed passive learners. We prove that the label complexity of the new algorithm is significantly lower than that of any passive learner with similar error guarantees. Our algorithm is based on a generalized sample compression scheme and a new label-efficient active model-selection procedure. Based on joint work with Aryeh Kontorovich and Ruth Urner.

Algebraic Geometry and Representation Theory Seminar

Date:
03
Tuesday
January
2017
Lecture / Seminar
Time: 11:15-12:30
Title: A geometric approach to Hall algebras
Location: Jacob Ziskind Building
Lecturer: Elena Gal
Organizer: Faculty of Mathematics and Computer Science
Abstract: The Hall algebra associated to a category can be constructed using the Waldhause ...The Hall algebra associated to a category can be constructed using the Waldhausen S-construction. We will give a systematic recipe for this and show how one can use it to construct higher associativity data. We will discuss a natural extension of this construction providing a bi-algebraic structure for Hall algebra. As a result we obtain a more transparent proof of Green's theorem about the bi-algebra structure on the Hall algebra.

Mathematical Analysis and Applications Seminar

Date:
03
Tuesday
January
2017
Lecture / Seminar
Time: 11:15-12:15
Title: On blow up and preventing of blow up of solutions of nonlinear dissipative PDE’s
Location: Jacob Ziskind Building
Lecturer: Varga Kalantarov
Organizer: Faculty of Mathematics and Computer Science
Abstract: We are going to discuss the impact of convective terms on the global solvability ...We are going to discuss the impact of convective terms on the global solvability or finite time blow up of solutions of initial boundary value problems for nonlinear dissipative PDEs. We will consider the model examples of 1D Burger's type equation, convective Cahn-Hilliard equation, generalized Kuramoto-Sivashinsky equation, generalized KdV type equations, and establish that sufficiently strong convective terms prevent solutions from blowing up in a finite time and make the considered systems globally well-posed and dissipative. We will also show that solutions of corresponding equations with weak enough convective terms may blow up in a finite time.

Foundations of Computer Science Seminar

Date:
02
Monday
January
2017
Lecture / Seminar
Time: 14:30-16:00
Title: Recent advances in randomness extractors and their applications
Location: Jacob Ziskind Building
Lecturer: Gil Cohen
Organizer: Faculty of Mathematics and Computer Science
Abstract: We present recent developments in randomness extractors theory and applications ...We present recent developments in randomness extractors theory and applications to classical, long-standing, open problems such as Ramsey graphs constructions and privacy amplification protocols. This exciting progress heavily relies on two new pseudo-random primitives we call correlation breakers and independence-preserving mergers, which we discuss.

Geometric Functional Analysis and Probability Seminar

Date:
29
Thursday
December
2016
Lecture / Seminar
Time: 11:00-13:00
Title: Gaussian complex zeros on the hole event: the emergence of a forbidden region
Location: Jacob Ziskind Building
Lecturer: Alon Nishry
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
27
Tuesday
December
2016
Lecture / Seminar
Time: 17:20
Title: TEST
Lecturer: test
Organizer: Faculty of Mathematics and Computer Science

Seminar in Geometry and Topology

Date:
27
Tuesday
December
2016
Lecture / Seminar
Time: 16:00-17:30
Title: On algebraic and diophantine geometry in characteristic 1
Location: Elaine and Bram Goldsmith Building for Mathematics and Computer Sciences
Lecturer: Boris Zilber
Organizer: Faculty of Mathematics and Computer Science
Abstract: I will start with a motivation of what algebraic (and model-theoretic) propertie ...I will start with a motivation of what algebraic (and model-theoretic) properties an algebraically closed field of characteristic 1 is expected to have. Then I will explain how a search of similar properties lead to a well-known now Hrushovski's construction and then formulate very precise properties that such a construction produces and so the field must satisfy. The axioms have a form of diophantine and valuation-theoretic statements in positive characteristics and the consistency of those remain an open problem. A special case of the axioms has been confirmed by a theorem of F.Bogomolov.

Algebraic Geometry and Representation Theory Seminar

Date:
27
Tuesday
December
2016
Lecture / Seminar
Time: 11:15-12:30
Title: P (n) via categorification of Temperley- Lieb algebra and Sp(infinity)
Location: Jacob Ziskind Building
Lecturer: Vera Serganova
Organizer: Faculty of Mathematics and Computer Science

Mathematical Analysis and Applications Seminar

Date:
27
Tuesday
December
2016
Lecture / Seminar
Time: 11:15-12:15
Title: Global existence for systems describing multicomponent reactive flow
Location: Jacob Ziskind Building
Lecturer: Martine Marion
Organizer: Faculty of Mathematics and Computer Science
Abstract: We consider combustion problems in the presence of complex chemistry and nonline ...We consider combustion problems in the presence of complex chemistry and nonlinear diffusion laws for the chemical species. The nonlinear diffusion coefficients are obtained by resolution of the so-called Stefan-Maxwell equations. We prove the existence of weak solutions for the corresponding system of equations which involves coupling between the incompressible Navier-Stokes and equations for temperature and species concentrations.

Seminar in Geometry and Topology

Date:
26
Monday
December
2016
Lecture / Seminar
Time: 16:15-17:45
Title: Optimal transport and geodesics on diffeomorphism groups
Location: Jacob Ziskind Building
Lecturer: Boris Khesin
Organizer: Faculty of Mathematics and Computer Science
Abstract: We revisit how the Euler and Burgers equations arise as geodesics on the groups ...We revisit how the Euler and Burgers equations arise as geodesics on the groups of diffeomorphisms. It turns out that the Euler hydrodynamics is in a sense dual to problems of optimal mass transport. We also describe L^2 and H^1 versions of the the Wasserstein space of volume forms. It turns out that for the homogeneous H^1 metric the Wasserstein space is isometric to (a piece of) an infinite-dimensional sphere and it leads to an integrable generalization of the Hunter-Saxton equation.

Foundations of Computer Science Seminar

Date:
26
Monday
December
2016
Lecture / Seminar
Time: 14:30-17:00
Title: Theory and applications of operator scaling
Location: Jacob Ziskind Building
Lecturer: Avi Wigderson
Organizer: Faculty of Mathematics and Computer Science

Machine Learning and Statistics Seminar

Date:
26
Monday
December
2016
Lecture / Seminar
Time: 11:45-12:45
Title: A Non-generative Framework and Convex Relaxations for Unsupervised Learning
Location: Jacob Ziskind Building
Lecturer: Elad Hazan
Organizer: Faculty of Mathematics and Computer Science
Abstract: We will describe a novel theoretical framework for unsupervised learning which i ...We will describe a novel theoretical framework for unsupervised learning which is not based on generative assumptions. It is comparative, and allows to avoid known computational hardness results and improper algorithms based on convex relaxations. We show how several families of unsupervised learning models, which were previously only analyzed under probabilistic assumptions and are otherwise provably intractable, can be efficiently learned in our framework by convex optimization. These includes dictionary learning and learning of algebraic manifolds. Joint work with Tengyu Ma. === Bio === Elad Hazan is a professor of computer science at Princeton university. His research focuses on the design and analysis of algorithms for basic problems in machine learning and optimization. Amongst his contributions are the co-development of the AdaGrad algorithm for training learning machines, and the first sublinear-time algorithms for convex optimization. He is the recipient of (twice) the IBM Goldberg best paper award in 2012 for contributions to sublinear time algorithms for machine learning, and in 2008 for decision making under uncertainty, a European Research Council grant, a Marie Curie fellowship and a Google Research Award (twice). He served on the steering committee of the Association for Computational Learning and has been program chair for COLT 2015.

Vision and Robotics Seminar

Date:
22
Thursday
December
2016
Lecture / Seminar
Time: 12:15-13:30
Title: Image colorization and its role in visual learning
Location: Jacob Ziskind Building
Lecturer: Greg Shakhnarovich
Organizer: Faculty of Mathematics and Computer Science
Abstract: I will present our recent and ongoing work on fully automatic image colorization ...I will present our recent and ongoing work on fully automatic image colorization. Our approach exploits both low-level and semantic representations during colorization. As many scene elements naturally appear according to multimodal color distributions, we train our model to predict per-pixel color histograms. This intermediate output can be used to automatically generate a color image, or further manipulated prior to image formation to "push" the image in a desired direction. Our system achieves state-of-the-art results under a variety of metrics. Moreover, it provides a vehicle to explore the role the colorization task can play as a proxy for visual understanding, providing a self-supervision mechanism for learning representations. I will describe the ability of our self-supervised network in several contexts, such as classification and semantic segmentation. On VOC segmentation and classification tasks, we present results that are state-of-the-art among methods not using ImageNet labels for pretraining. Joint work with Gustav Larsson and Michael Maire.

Seminar in Geometry and Topology

Date:
20
Tuesday
December
2016
Lecture / Seminar
Time: 16:00-17:30
Title: Schwartz functions on real algebraic varieties
Location: The David Lopatie Hall of Graduate Studies
Lecturer: Boaz Elazar
Organizer: Faculty of Mathematics and Computer Science
Abstract: We define Schwartz functions and tempered functions on affine real algebraic var ...We define Schwartz functions and tempered functions on affine real algebraic varieties, which might be singular. We prove that some of the important classical properties of these functions, such as partition of unity, characterization on open subsets, etc., continue to hold in this case. Some of our proves are based on the works of Milman, Bierstone and Pawlucki on Whitney's extension problem and composite differentiable functions. Joint work with Ary Shaviv.

Mathematical Analysis and Applications Seminar

Date:
20
Tuesday
December
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Dynamical Cell Complexes: Evolution, Universality, and Statistics
Location: Jacob Ziskind Building
Lecturer: Emanuel A. Lazar
Organizer: Faculty of Mathematics and Computer Science
Abstract: Many physical and biological systems are cellular in nature -- soap foams, biolo ...Many physical and biological systems are cellular in nature -- soap foams, biological tissue, and polycrystalline metals are but a few examples that we encounter in everyday life. Many of these systems evolve in a manner that changes their geometries and topologies to lower some global energy. We use computer simulations to study how mean curvature flow shapes cellular structures in two and three dimensions. This research touches on discrete geometric flows, combinatorial polyhedra and their symmetries, and the quantification of topological features of large cellular systems. If time permits, I will also describe some exact results in 1 dimension.

Algebraic Geometry and Representation Theory Seminar

Date:
20
Tuesday
December
2016
Lecture / Seminar
Time: 11:15-12:30
Title: On a bizarre geometric property of a counterexample to the Jacobian conjecture
Location: Jacob Ziskind Building
Lecturer: Leonid Makar-Limanov
Organizer: Faculty of Mathematics and Computer Science

Guest Seminar

Date:
20
Tuesday
December
2016
Lecture / Seminar
Time: 11:00-12:30
Title: Learning to act from observational data
Location: Elaine and Bram Goldsmith Building for Mathematics and Computer Sciences
Lecturer: Uri Shalit
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
19
Monday
December
2016
Lecture / Seminar
Time: 14:30-16:00
Title: Robust sensitivity
Location: Jacob Ziskind Building
Lecturer: Shachar Lovett
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
15
Thursday
December
2016
Lecture / Seminar
Time: 12:15-13:30
Title: Calibration of Multi-Camera Systems by Global Constraints on the Motion of Silhouettes
Location: Jacob Ziskind Building
Lecturer: Gil Ben-Artzi
Organizer: Faculty of Mathematics and Computer Science
Abstract: Computing the epipolar geometry between cameras with very different viewpoints i ...Computing the epipolar geometry between cameras with very different viewpoints is often problematic as matching points are hard to find. In these cases, it has been proposed to use information from dynamic objects in the scene for suggesting point and line correspondences. We introduce an approach that improves by two orders of magnitude the performance over state-of-the-art methods, by significantly reducing the number of outliers in the putative matches. Our approach is based on (a) a new temporal signature: motion barcode, which is used to recover corresponding epipolar lines across views, and (b) formulation of the correspondences problem as constrained flow optimization, requiring small differences between the coordinates of corresponding points over consecutive frames. Our method was validated on four standard datasets providing accurate calibrations across very different viewpoints.

Geometric Functional Analysis and Probability Seminar

Date:
15
Thursday
December
2016
Lecture / Seminar
Time: 11:00-13:00
Title: Symbolic dynamics for non uniformly hyperbolic diffeomorphisms of compact smooth manifolds
Location: Jacob Ziskind Building
Lecturer: Snir Ben Ovadia
Organizer: Faculty of Mathematics and Computer Science

Machine Learning and Statistics Seminar

Date:
14
Wednesday
December
2016
Lecture / Seminar
Time: 11:15-12:15
Title: Online Learning with Feedback Graphs Without the Graphs
Location: Jacob Ziskind Building
Lecturer: Alon Cohen
Organizer: Faculty of Mathematics and Computer Science

Seminar in Geometry and Topology

Date:
13
Tuesday
December
2016
Lecture / Seminar
Time: 16:00-17:30
Title: On the Gevrey regularity of CR-mappings
Location: Elaine and Bram Goldsmith Building for Mathematics and Computer Sciences
Lecturer: Ilya Kossovskiy
Organizer: Faculty of Mathematics and Computer Science

Mathematical Analysis and Applications Seminar

Date:
13
Tuesday
December
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Non-Euclidean elasticity and asymptotic rigidity of manifolds
Location: Jacob Ziskind Building
Lecturer: Cy Maor
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
13
Tuesday
December
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Canonical bases in quantum Schubert cells
Location: Jacob Ziskind Building
Lecturer: Arkady Berenstein
Organizer: Faculty of Mathematics and Computer Science
Abstract: The goal of my talk (based on a recent joint paper with Jacob Greenstein) is to ...The goal of my talk (based on a recent joint paper with Jacob Greenstein) is to provide an elementary construction of the canonical basis B(w) in each quantum Schubert cell U_q(w) and to establish its invariance under Lusztig's symmetries. In particular, I will explain how to directly construct the upper global basis B^up, will show that B(w) is contained in B^up, and that a large part of the latter is preserved by the (modified) Lusztig's symmetries.

Algebraic Geometry and Representation Theory Seminar

Date:
13
Tuesday
December
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Finite-dimensional representations of quantum affine algebras
Location: Jacob Ziskind Building
Lecturer: Jianrong Li
Organizer: Faculty of Mathematics and Computer Science
Abstract: In this talk, I will talk about finite dimensional representations of quantum af ...In this talk, I will talk about finite dimensional representations of quantum affine algebras. The main topics are Chari and Presslay's classification of finite-dimensional simple modules over quantum affine algebras, Frenkel and Reshetikhin's theory of q-characters of finite dimensional modules, Frenkel-Mukhin algorithm to compute q-characters, T-systems, Hernandez-Leclerc's conjecture about the cluster algebra structure on the ring of a subcategory of the category of all finite dimensional representations of a quantum affine algebra. I will also talk about how to obtain a class of simple modules called minimal affinizations of types A, B using mutations (joint work with Bing Duan, Yanfeng Luo, Qianqian Zhang).

Foundations of Computer Science Seminar

Date:
12
Monday
December
2016
Lecture / Seminar
Time: 14:30-16:00
Title: Optimal Resilience for Short-Circuit Noise in Formulas
Location: Jacob Ziskind Building
Lecturer: Ran Gelles
Organizer: Faculty of Mathematics and Computer Science

Guest Seminar

Date:
08
Thursday
December
2016
Lecture / Seminar
Time: 12:00-13:30
Title: From Programming Languages to Programming Systems – Software Development by Refinement
Location: Jacob Ziskind Building
Lecturer: Shachar Itzhaky
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
06
Tuesday
December
2016
Lecture / Seminar
Time: 11:15-12:30
Title: The Duflo-Serganova functor and character rings of Lie superalgebras
Location: Jacob Ziskind Building
Lecturer: Crystal Hoyt
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
05
Monday
December
2016
Lecture / Seminar
Time: 14:30-16:00
Title: Grassmann Graphs, Vertex Cover and 2-to-2 games
Location: Jacob Ziskind Building
Lecturer: Dor Minzer
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
01
Thursday
December
2016
Lecture / Seminar
Time: 12:15-13:30
Title: Applications of Subspace and Low-Rank Methods for Dynamic and Multi-Contrast Magnetic Resonance Imaging
Location: Jacob Ziskind Building
Lecturer: Michael (Miki) Lustig
Organizer: Faculty of Mathematics and Computer Science
Abstract: There has been much work in recent years to develop methods for recovering signa ...There has been much work in recent years to develop methods for recovering signals from insufficient data. One very successful direction are subspace methods that constrain the data to live in a lower dimensional space. These approaches are motivated by theoretical results in recovering incomplete low-rank matrices as well as exploiting the natural redundancy of multidimensional signals. In this talk I will present our research group's efforts in this area. I will start with describing a new decomposition that can represent dynamic images as a sum of multi-scale low-rank matrices, which can very efficiently capture spatial and temporal correlations in multiple scales. I will then describe and show results from applications using subspace and low-rank methods for highly accelerated multi-contrast MR imaging and for the purpose of motion correction.

Mathematical Analysis and Applications Seminar

Date:
29
Tuesday
November
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Boundary triples and Weyl functions of symmetric operators
Location: Jacob Ziskind Building
Lecturer: Volodymyr Derkach
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
29
Tuesday
November
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Whittaker supports of representations of reductive groups
Location: Jacob Ziskind Building
Lecturer: Dmitry Gourevitch
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
28
Monday
November
2016
Lecture / Seminar
Time: 14:30-16:00
Title: Computational Efficiency Requires Simple Taxation
Location: Jacob Ziskind Building
Lecturer: Shahar Dobzinski
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
27
Sunday
November
2016
Lecture / Seminar
Time: 12:15-13:30
Title: New Hardness Results for Routing on Disjoint Paths
Location: Jacob Ziskind Building
Lecturer: Julia Chuzhoy
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
22
Tuesday
November
2016
Lecture / Seminar
Time: 11:15-12:30
Title: An affine version of Robinson-Schensted Correspondence for Kazhdan-Lusztig theory
Location: Jacob Ziskind Building
Lecturer: Michael Chmutov
Organizer: Faculty of Mathematics and Computer Science
Abstract: In his study of Kazhdan-Lusztig cells in affine type A, Shi has introduced an af ...In his study of Kazhdan-Lusztig cells in affine type A, Shi has introduced an affine analog of Robinson-Schensted Correspondence. We generalize the Matrix-Ball Construction of Viennot and Fulton to give a more combinatorial realization of Shi's algorithm. As a byproduct, we also give a way to realize the affine correspondence via the usual Robinson-Schensted bumping algorithm. Next, inspired by Honeywill, we extend the algorithm to a bijection between the extended affine symmetric group and collection of triples (P, Q, r) where P and Q are tabloids and r is a dominant weight.

Mathematical Analysis and Applications Seminar

Date:
22
Tuesday
November
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Mathematical Challenges in Submonolayer Deposition
Location: Jacob Ziskind Building
Lecturer: Michael Grinfeld
Organizer: Faculty of Mathematics and Computer Science
Abstract: Submonolayer deposition (SD) is a blanket term used to describe the initial stag ...Submonolayer deposition (SD) is a blanket term used to describe the initial stages of processes, such as molecular beam epitaxy, in which material is deposited onto a surface, diffuses and forms large-scale structures. It is easy to simulate using Monte Carlo methods, but theoretical results are few and far between. I will discuss various approaches to SD in the 1-dimensional situation, focusing on open mathematical problems and the difficulty of passing to the 2-dimensional case, which is of most applied interest. This is mainly joint work with Paul Mulheran.

Foundations of Computer Science Seminar

Date:
21
Monday
November
2016
Lecture / Seminar
Time: 14:30-16:00
Title: Memory-Efficient Algorithms for Finding Needles in Haystacks
Location: Jacob Ziskind Building
Lecturer: Adi Shamir
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
21
Monday
November
2016
Lecture / Seminar
Time: 12:15-13:15
Title: Spectral Approaches to Partial Shape Matching
Location: Jacob Ziskind Building
Lecturer: Emanuele Rodola', Or Litany
Organizer: Faculty of Mathematics and Computer Science
Abstract: In this talk we will present our recent line of work on (deformable) partial sha ...In this talk we will present our recent line of work on (deformable) partial shape correspondence in the spectral domain. We will first introduce Partial Functional Maps (PFM), showing how to robustly formulate the shape correspondence problem under missing geometry with the language of functional maps. We use perturbation analysis to show how removal of shape parts changes the Laplace-Beltrami eigenfunctions, and exploit it as a prior on the spectral representation of the correspondence. We will show further extensions to deal with the presence of clutter (deformable object-in-clutter) and multiple pieces (non-rigid puzzles). In the second part of the talk, we will introduce a novel approach to the same problem which operates completely in the spectral domain, avoiding the cumbersome alternating optimization used in the previous approaches. This allows matching shapes with constant complexity independent of the number of shape vertices, and yields state-of-the-art results on challenging correspondence benchmarks in the presence of partiality and topological noise.

Geometric Functional Analysis and Probability Seminar

Date:
17
Thursday
November
2016
Lecture / Seminar
Time: 11:00-13:00
Title: Invertibility of sparse random matrices
Location: Jacob Ziskind Building
Lecturer: Anirban Basak
Organizer: Faculty of Mathematics and Computer Science
Abstract: We consider a class of sparse random matrices of the form $A_n =(xi_{i,j}delta_{ ...We consider a class of sparse random matrices of the form $A_n =(xi_{i,j}delta_{i,j})_{i,j=1}^n$, where ${xi_{i,j}}$ are i.i.d.~centered random variables, and ${delta_{i,j}}$ are i.i.d.~Bernoulli random variables taking value $1$ with probability $p_n$, and prove a quantitative estimate on the smallest singular value for $p_n = Omega(frac{log n}{n})$, under a suitable assumption on the spectral norm of the matrices. This establishes the invertibility of a large class of sparse matrices. We also find quantitative estimates on the smallest singular value of the adjacency matrix of a directed Erdos-Reyni graph whenever its edge connectivity probability is above the critical threshold $Omega(frac{log n}{n})$. This is joint work with Mark Rudelson.

Machine Learning and Statistics Seminar

Date:
16
Wednesday
November
2016
Lecture / Seminar
Time: 11:15-12:15
Title: Faster Projection-free Machine Learning and Optimization
Location: Jacob Ziskind Building
Lecturer: Dan Garber
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
15
Tuesday
November
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Derived adic completion of commutative DG-rings
Location: Jacob Ziskind Building
Lecturer: Liran Shaul
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
14
Monday
November
2016
Lecture / Seminar
Time: 14:30-16:00
Title: Algebraic Attacks against Random Local Functions and Their Countermeasures
Location: Jacob Ziskind Building
Lecturer: Benny Applebaum
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
10
Thursday
November
2016
Lecture / Seminar
Time: 12:15-13:30
Title: End-to-End Learning: Applications in Speech, Vision and Cognition
Location: Jacob Ziskind Building
Lecturer: Yedid Hoshen
Organizer: Faculty of Mathematics and Computer Science

Geometric Functional Analysis and Probability Seminar

Date:
03
Thursday
November
2016
Lecture / Seminar
Time: 11:00-13:00
Title: Some applications of the $p$-biased measure to ErdH{o}s-Ko-Rado type problems
Location: Jacob Ziskind Building
Lecturer: David Ellis
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
01
Tuesday
November
2016
Lecture / Seminar
Time: 11:15-12:30
Title: S-graphs, trails and identities in Demazure modules
Location: Jacob Ziskind Building
Lecturer: Anthony Joseph
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
31
Monday
October
2016
Lecture / Seminar
Time: 14:30-16:00
Title: Constant-Round Interactive Proofs for Delegating Computation
Location: Jacob Ziskind Building
Lecturer: Guy Rothblum
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
26
Monday
September
2016
Lecture / Seminar
Time: 14:00-15:30
Title: From the Optics Lab to Computer Vision
Location: Jacob Ziskind Building
Lecturer: Achuta Kadambi
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
21
Wednesday
September
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Introduction to cluster algebras (continuation)
Location: Jacob Ziskind Building
Lecturer: Jian-Rong Li
Organizer: Faculty of Mathematics and Computer Science
Abstract: Cluster algebras are a class of commutative rings introduced by Fomin and Zelevi ...Cluster algebras are a class of commutative rings introduced by Fomin and Zelevinsky in 2000. I will give an introductory talk about cluster algebras. The main examples are the cluster algebra of type A2, the coordinate ring of $SL_4/N$, and the homogeneous coordinate ring of the Grassmannian $Gr_{2,n 3}(mathbb{C})$.

Algebraic Geometry and Representation Theory Seminar

Date:
14
Wednesday
September
2016
Lecture / Seminar
Time: 11:00-12:30
Title: Introduction to cluster algebras
Location: Jacob Ziskind Building
Lecturer: Jian-Rong Li
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
08
Thursday
September
2016
Lecture / Seminar
Time: 12:15-13:30
Title: Exploring and Modifying Spatial Variations in a Single Image
Location: Jacob Ziskind Building
Lecturer: Tali Dekel
Organizer: Faculty of Mathematics and Computer Science
Abstract: Structures and objects, captured in image data, are often idealized by the viewe ...Structures and objects, captured in image data, are often idealized by the viewer. For example, buildings may seem to be perfectly straight, or repeating structures such as corn's kernels may seem almost identical. However, in reality, such flawless behavior hardly exists. The goal in this line of work is to detect the spatial imperfection, i.e., departure of objects from their idealized models, given only a single image as input, and to render a new image in which the deviations from the model are either reduced or magnified. Reducing the imperfections allows us to idealize/beautify images, and can be used as a graphic tool for creating more visually pleasing images. Alternatively, increasing the spatial irregularities allow us to reveal useful and surprising information that is hard to visually perceive by the naked eye (such as the sagging of a house's roof). I will consider this problem under two distinct definitions of idealized model: (i) ideal parametric geometries (e.g., line segments, circles), which can be automatically detected in the input image. (ii) perfect repetitions of structures, which relies on the redundancy of patches in a single image. Each of these models has lead to a new algorithm with a wide range of applications in civil engineering, astronomy, design, and materials defects inspection.

Seminar in Geometry and Topology

Date:
23
Tuesday
August
2016
Lecture / Seminar
Time: 16:00-17:30
Title: Homogeneous dynamic, hyperbolic geometry and cone conjecture
Location: Jacob Ziskind Building
Lecturer: Misha Verbitsky
Organizer: Faculty of Mathematics and Computer Science
Abstract: Hyperbolic manifold is a Riemannian manifold of constant negative curvature and ...Hyperbolic manifold is a Riemannian manifold of constant negative curvature and finite volume. Let S be a set of geodesic hypersurfaces in a hyperbolic manifold of dimension >2. Using Ratner theory, we prove that either S is dense, or it is finite. This is used to study the Kahler cone of a holomorphically symplectic manifold. It turns out that the shape of the Kahler cone is encoded in the geometry of a certain polyhedron in a hyperbolic manifold. I will explain how this correspondence works, and how it is used to obtain the cone conjecture of Kawamata and Morrison. This is a joint work with Ekaterina Amerik.

Vision and Robotics Seminar

Date:
04
Thursday
August
2016
Lecture / Seminar
Time: 11:30-13:00
Title: Scalable Locally Injective Mappings
Location: Jacob Ziskind Building
Lecturer: Michael Rabinovich
Organizer: Faculty of Mathematics and Computer Science
Abstract: We present a scalable approach for the optimization of flip-preventing energies ...We present a scalable approach for the optimization of flip-preventing energies in the general context of simplicial mappings, and specifically for mesh parameterization. Our iterative minimization is based on the observation that many distortion energies can be optimized indirectly by minimizing a simpler proxy energy and compensating for the difference with a reweighting scheme. Our algorithm is simple to implement and scales to datasets with millions of faces. We demonstrate our approach for the computation of maps that minimize a conformal or isometric distortion energy, both in two and three dimensions. In addition to mesh parameterization, we show that our algorithm can be applied to mesh deformation and mesh quality improvement.

Algebraic Geometry and Representation Theory Seminar

Date:
03
Wednesday
August
2016
Lecture / Seminar
Time: 10:30-12:00
Title: The Capelli problem for gl(m|n) and the spectrum of invariant differential operators
Location: Jacob Ziskind Building
Lecturer: Siddhartha Sahi
Organizer: Faculty of Mathematics and Computer Science
Abstract: The "generalized" Capelli operators form a linear basis for the ring of invarian ...The "generalized" Capelli operators form a linear basis for the ring of invariant differential operators on symmetric cones, such as GL/O and GL/Sp. The Harish-Chandra images of these operators are specializations of certain polynomials defined by speaker and studied together with F. Knop. These "Knop-Sahi" polynomials are inhomogeneous polynomials characterized by simple vanishing conditions

Vision and Robotics Seminar

Date:
18
Monday
July
2016
Lecture / Seminar
Time: 11:30-13:00
Title: Voronoi topology analysis of structure in spatial point sets
Location: Jacob Ziskind Building
Lecturer: Emanuel A. Lazar
Organizer: Faculty of Mathematics and Computer Science
Abstract: Atomic systems are regularly studied as large sets of point-like particles, and ...Atomic systems are regularly studied as large sets of point-like particles, and so understanding how particles can be arranged in such systems is a very natural problem. However, aside from perfect crystals and ideal gases, describing this kind of "structure" in an insightful yet tractable manner can be challenging. Analysis of the configuration space of local arrangements of neighbors, with some help from the Borsuk-Ulam theorem, helps explain limitations of continuous metric approaches to this problem, and motivates the use of Voronoi cell topology. Several short examples from materials research help illustrate strengths of this approach.

Vision and Robotics Seminar

Date:
14
Thursday
July
2016
Lecture / Seminar
Time: 12:15-13:30
Title: SIGGRAPH Dry-Runs
Location: Jacob Ziskind Building
Lecturer: Netalee Efrat and Meirav Galun
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
29
Wednesday
June
2016
Lecture / Seminar
Time: 11:15-12:15
Title: The singular transfer for the Jacquet-Rallis trace formula
Location: Jacob Ziskind Building
Lecturer: Michal Zydor
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
26
Sunday
June
2016
Lecture / Seminar
Time: 14:30-16:00
Title: An Exponential Separation Between Randomized and Deterministic Complexity in the LOCAL Model
Location: The David Lopatie Hall of Graduate Studies
Lecturer: Yi-Jun Chang
Organizer: Faculty of Mathematics and Computer Science
Abstract: Over the past 30 years numerous algorithms have been designed for symmetry break ...Over the past 30 years numerous algorithms have been designed for symmetry breaking problems in the LOCAL model, such as maximal matching, MIS, vertex coloring, and edge-coloring. For most problems the best randomized algorithm is at least exponentially faster than the best deterministic algorithm. In this paper we prove that these exponential gaps are necessary and establish connections between the deterministic and randomized complexities in the LOCAL model. Each result has a very compelling take-away message: 1. Fast Δ-coloring of trees requires random bits: Building on the recent lower bounds of Brandt et al., we prove that the randomized complexity of Δ-coloring a tree with maximum degree Δ≥55 is Θ(log_Δ log n), whereas its deterministic complexity is Θ(log_Δ n) for any Δ≥3. This also establishes a large separation between the deterministic complexity of Δ-coloring and (Δ 1)-coloring trees. 2. Randomized lower bounds imply deterministic lower bounds: We prove that any deterministic algorithm for a natural class of problems that runs in O(1) o(log_Δ n) rounds can be transformed to run in O(log*n −log*Δ 1) rounds. If the transformed algorithm violates a lower bound (even allowing randomization), then one can conclude that the problem requires Ω(log_Δ n) time deterministically. 3. Deterministic lower bounds imply randomized lower bounds: We prove that the randomized complexity of any natural problem on instances of size n is at least its deterministic complexity on instances of size √ log n. This shows that a deterministic Ω(log_Δ n) lower bound for any problem implies a randomized Ω(log_Δ log n) lower bound. It also illustrates that the graph shattering technique is absolutely essential to the LOCAL model.

Geometric Functional Analysis and Probability Seminar

Date:
23
Thursday
June
2016
Lecture / Seminar
Time: 12:00-13:00
Title: Small Representations of Finite Classical Groups
Location: Jacob Ziskind Building
Lecturer: Shamgar Gurevich
Organizer: Faculty of Mathematics and Computer Science
Abstract: Many properties of a finite group G can be approached using formulas involving s ...Many properties of a finite group G can be approached using formulas involving sums over its characters. A serious obstacle in applying these formulas seemed to be lack of knowledge over the low dimensional representations of G. In fact, the "small" representations tend to contribute the largest terms to these sums, so a systematic knowledge of them might lead to proofs of some conjectures which are currently out of reach.

Geometric Functional Analysis and Probability Seminar

Date:
23
Thursday
June
2016
Lecture / Seminar
Time: 11:15-12:00
Title: L_2 Mixing and hypercontractivity via maximal inequalities and hitting-times
Location: Jacob Ziskind Building
Lecturer: Jonathan Hermon
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
22
Wednesday
June
2016
Lecture / Seminar
Time: 11:15-12:30
Title: The intricate Maze of Graph Complexes
Location: Jacob Ziskind Building
Lecturer: Vasily Dolgushev
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
16
Thursday
June
2016
Lecture / Seminar
Time: 14:00-15:30
Title: Representations of reductive groups distinguished by symmetric subgroups
Location: Jacob Ziskind Building
Lecturer: Itay Glazer
Organizer: Faculty of Mathematics and Computer Science

Vision and Robotics Seminar

Date:
16
Thursday
June
2016
Lecture / Seminar
Time: 12:15-13:30
Title: .
Location: Jacob Ziskind Building
Lecturer: Yair Weiss
Organizer: Faculty of Mathematics and Computer Science
Abstract: TBA ...TBA

Vision and Robotics Seminar

Date:
16
Thursday
June
2016
Lecture / Seminar
Time: 12:15-13:30
Title: Neural Networks, Graphical Models and Image Restoration
Location: Jacob Ziskind Building
Lecturer: Yair Weiss
Organizer: Faculty of Mathematics and Computer Science
Abstract: This is an invited talk I gave last year at a workshop on "Deep Learning for Vis ...This is an invited talk I gave last year at a workshop on "Deep Learning for Vision". It discusses some of the history of graphical models and neural networks and speculates on the future of both fields with examples from the particular problem of image restoration.

Geometric Functional Analysis and Probability Seminar

Date:
16
Thursday
June
2016
Lecture / Seminar
Time: 12:00-13:00
Title: Critical points and the Gibbs measure of pure spherical spin glasses
Location: Jacob Ziskind Building
Lecturer: Eliran Subag
Organizer: Faculty of Mathematics and Computer Science
Abstract: Recently, several results concerning the critical points of the energy landscape ...Recently, several results concerning the critical points of the energy landscape of pure $p$-spin spherical spin glasses have been obtained by means of moment computations and a proof of a certain invariance property. I will describe those and explain how they can be boosted by an investigation of the behavior around the critical points to obtain a geometric description for the Gibbs measure at low enough temperature. The talk is based on joint work with Ofer Zeitouni.

Geometric Functional Analysis and Probability Seminar

Date:
16
Thursday
June
2016
Lecture / Seminar
Time: 11:15-12:00
Title: Can one hear the shape of a random walk?
Location: Jacob Ziskind Building
Lecturer: Eviatar Procaccia
Organizer: Faculty of Mathematics and Computer Science
Abstract: We consider a Gibbs distribution over random walk paths on the square lattice, p ...We consider a Gibbs distribution over random walk paths on the square lattice, proportional to a random weight of the path's boundary. We show that in the zero temperature limit, the paths condensate around an asymptotic shape. This limit shape is characterized as the minimizer of the functional, mapping open connected subsets of the plane to the sum of their principle eigenvalue and perimeter (with respect to the first passage percolation norm). A prime novel feature of this limit shape is that it is not in the class of Wulff shapes. Joint work with Marek Biskup.

Algebraic Geometry and Representation Theory Seminar

Date:
15
Wednesday
June
2016
Lecture / Seminar
Time: 11:15-12:30
Title: A minimax theorem for trails
Location: Jacob Ziskind Building
Lecturer: Anthony Joseph
Organizer: Faculty of Mathematics and Computer Science

The Chaim Leib Pekeris Memorial Lecture

Date:
14
Tuesday
June
2016
Lecture / Seminar
Time: 11:30-13:00
Title: The Quantum Computer Puzzle
Lecturer: Gil Kalai
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
08
Wednesday
June
2016
Lecture / Seminar
Time: 11:15-12:15
Title: Supersingular representations and the mod p Langlands
Location: Jacob Ziskind Building
Lecturer: Yotam Hendel
Organizer: Faculty of Mathematics and Computer Science

Machine Learning and Statistics Seminar

Date:
08
Wednesday
June
2016
Lecture / Seminar
Time: 11:15-12:15
Title: No bad local minima: Data independent training error guarantees for multilayer neural networks
Location: Jacob Ziskind Building
Lecturer: Daniel Soudry
Organizer: Faculty of Mathematics and Computer Science
Abstract: We use smoothed analysis techniques to provide guarantees on the training loss o ...We use smoothed analysis techniques to provide guarantees on the training loss of Multilayer Neural Networks (MNNs) at differentiable local minima. Specifically, we examine MNNs with piecewise linear activation functions, quadratic loss and a single output, under mild over-parametrization. We prove that for a MNN with one hidden layer, the training error is zero at every differentiable local minimum, for almost every dataset and dropout-like noise realization. We then extend these results to the case of more than one hidden layer. Our theoretical guarantees assume essentially nothing on the training data, and are verified numerically. These results suggest why the highly non-convex loss of such MNNs can be easily optimized using local updates (e.g., stochastic gradient descent), as observed empirically.

Seminar in Geometry and Topology

Date:
07
Tuesday
June
2016
Lecture / Seminar
Time: 16:00-17:30
Title: On periodic orbits in complex planar billiards
Location: Jacob Ziskind Building
Lecturer: Alexey Glutsyuk
Organizer: Faculty of Mathematics and Computer Science
Abstract: A conjecture of Victor Ivrii (1980) says that in every billiard with smooth boun ...A conjecture of Victor Ivrii (1980) says that in every billiard with smooth boundary the set of periodic orbits has measure zero. This conjecture is closely related to spectral theory. Its particular case for triangular orbits was proved by M. Rychlik (1989, in two dimensions), Ya. Vorobets (1994, in any dimension) and other mathematicians. The case of quadrilateral orbits in dimension two was treated in our joint work with Yu. Kudryashov (2012). We study the complexified version of planar Ivrii's conjecture with reflections from a collection of planar holomorphic curves. We present the classification of complex counterexamples with four reflections and partial positive results. The recent one says that a billiard on one irreducible complex algebraic curve without too complicated singularities cannot have a two-dimensional family of periodic orbits of any period. The above complex results have applications to other problems on real billiards: Tabachnikov's commuting billiard problem and Plakhov's invisibility conjecture.

Vision and Robotics Seminar

Date:
02
Thursday
June
2016
Lecture / Seminar
Time: 12:15-13:30
Title: Advection-based Function Matching on Surfaces
Location: Jacob Ziskind Building
Lecturer: Omri Azencot
Organizer: Faculty of Mathematics and Computer Science
Abstract: A tangent vector field on a surface is the generator of a smooth family of maps ...A tangent vector field on a surface is the generator of a smooth family of maps from the surface to itself, known as the flow. Given a scalar function on the surface, it can be transported, or advected, by composing it with a vector field's flow. Such transport is exhibited by many physical phenomena, e.g., in fluid dynamics. In this paper, we are interested in the inverse problem: given source and target functions, compute a vector field whose flow advects the source to the target. We propose a method for addressing this problem, by minimizing an energy given by the advection constraint together with a regularizing term for the vector field. Our approach is inspired by a similar method in computational anatomy, known as LDDMM, yet leverages the recent framework of functional vector fields for discretizing the advection and the flow as operators on scalar functions. The latter allows us to efficiently generalize LDDMM to curved surfaces, without explicitly computing the flow lines of the vector field we are optimizing for. We show two approaches for the solution: using linear advection with multiple vector fields, and using non-linear advection with a single vector field. We additionally derive an approximated gradient of the corresponding energy, which is based on a novel vector field transport operator. Finally, we demonstrate applications of our machinery to intrinsic symmetry analysis, function interpolation and map improvement.

Machine Learning and Statistics Seminar

Date:
01
Wednesday
June
2016
Lecture / Seminar
Time: 11:15-12:15
Title: Deep Learning and Semantic Interpretation of Natural Language
Location: Jacob Ziskind Building
Lecturer: Shalom Lappin
Organizer: Faculty of Mathematics and Computer Science
Abstract: Classical approaches to formal and computational semantics assign values to the ...Classical approaches to formal and computational semantics assign values to the terminal elements of hierarchical syntactic structures and define combinatorial operations on the semantic representations of phrases to compute the values of sentences. While these approaches offer formally elegant models of interpretation, they have not produced wide coverage systems. They do not provide for semantic learning. They have also not succeeded in integrating lexical and compositional semantics in an interesting or computationally efficient way. Recent developments in image caption generation suggest an alternative approach, which can overcome these difficulties. This work formulates the problem of matching images with descriptions as a task in machine translation. Deep neural networks use an encoder to map regions of pixels in an image to vector representations of graphic features, and a decoder to align these features with the distributional vectors of lexical and phrasal items. This approach can be generalized to deep neural networks that identify correspondences between multi-modal data structures and sentences. To the extent that this research program is successful, it will satisfy the core objective of the classical formal semantic program. It will assign truth (fulfilment) conditions to the sentences of a language, where these conditions are specified in terms of multi-modal representations of situations (scenes) in the world. These correspondences are generated not by a recursive definition of a truth predicate in a formal semantic theory, but by an extended deep neural language model.

Seminar in Geometry and Topology

Date:
31
Tuesday
May
2016
Lecture / Seminar
Time: 16:00-18:00
Title: Topological Galois theory
Location: Jacob Ziskind Building
Lecturer: Askold Khovanskii
Organizer: Faculty of Mathematics and Computer Science
Abstract: In the topological Galois theory we consider functions representable by quadratu ...In the topological Galois theory we consider functions representable by quadratures as multivalued analytical functions of one complex variable. It turns out that there are some topological restrictions on the way the Riemann surface of a function representable by quadratures can be positioned over the complex plan. If a function does not satisfy these restrictions, then it cannot be represented by quadratures. This approach, besides its geometrical appeal, has the following advantage. The topological obstructions are related to the character of a multivalued function. They hold not only for functions representable by quadratures, but also for a more wide class of functions. This class is obtained adding to the functions representable by quadratures all meromorphic functions and allowing the presence of such functions in all formulae. Hence the topological results on the non representability by quadratures are stronger that those of algebraic nature.

Foundations of Computer Science Seminar

Date:
30
Monday
May
2016
Lecture / Seminar
Time: 14:30-16:00
Title: Two Applications of Communication Complexity in Distributed Computing
Location: Jacob Ziskind Building
Lecturer: Rotem Oshman
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
26
Thursday
May
2016
Lecture / Seminar
Time: 14:00-15:15
Title: Ordered tensor categories of representations of Mackey Lie algebras
Location: Jacob Ziskind Building
Lecturer: Ivan Penkov
Organizer: Faculty of Mathematics and Computer Science
Abstract: TBA ...TBA

Vision and Robotics Seminar

Date:
25
Wednesday
May
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Visually Indicated Sounds
Location: Jacob Ziskind Building
Lecturer: Bill Freeman
Organizer: Faculty of Mathematics and Computer Science
Abstract: TBA ...TBA

Algebraic Geometry and Representation Theory Seminar

Date:
25
Wednesday
May
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Primitive ideals in U(sl(infinity))
Location: Jacob Ziskind Building
Lecturer: Ivan Penkov
Organizer: Faculty of Mathematics and Computer Science

Seminar in Geometry and Topology

Date:
24
Tuesday
May
2016
Lecture / Seminar
Time: 16:15-17:30
Title: Towards the global bifurcation theory on the plane
Location: Jacob Ziskind Building
Lecturer: Yu. Ilyashenko
Organizer: Faculty of Mathematics and Computer Science
Abstract: The talk provides a new perspective of the global bifurcation theory on the pla ...The talk provides a new perspective of the global bifurcation theory on the plane. Theory of planar bifurcations consists of three parts: local, nonlocal and global ones. It is now clear that the latter one is yet to be created. Local bifurcation theory (in what follows we will talk about the plane only) is related to transfigurations of phase portraits of differential equations near their singular points. This theory is almost completed, though recently new open problems occurred. Nonlocal theory is related to bifurcations of separatrix polygons (polycycles). Though in the last 30 years there were obtained many new results, this theory is far from being completed. Recently it was discovered that nonlocal theory contains another substantial part: a global theory. New phenomena are related with appearance of the so called sparkling saddle connections. The aim of the talk is to give an outline of the new theory and discuss numerous open problems. The main new results are: existence of an open set of structurally unstable families of planar vector fields, and of families having functional invariants (joint results with Kudryashov and Schurov). Thirty years ago Arnold stated six conjectures that outlined the future development of the global bifurcation theory in the plane. All these conjectures are now disproved. Though the theory develops in quite a different direction, this development is motivated by the Arnold's conjectures.

Foundations of Computer Science Seminar

Date:
23
Monday
May
2016
Lecture / Seminar
Time: 14:30-16:00
Title: Beating CountSketch for heavy hitters in insertion streams
Location: Jacob Ziskind Building
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
23
Monday
May
2016
Lecture / Seminar
Time: 14:30-16:00
Title: Beating CountSketch for heavy hitters in insertion streams
Location: Jacob Ziskind Building
Lecturer: Stephen Chestnut
Organizer: Faculty of Mathematics and Computer Science

Machine Learning and Statistics Seminar

Date:
18
Wednesday
May
2016
Lecture / Seminar
Time: 11:15-12:15
Title: Explaining the Success of AdaBoost and Random Forests as Interpolating Classifiers
Location: Jacob Ziskind Building
Lecturer: Abraham Wyner
Organizer: Faculty of Mathematics and Computer Science

Algebraic Geometry and Representation Theory Seminar

Date:
18
Wednesday
May
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Singular Gelfand-Tsetlin modules
Location: Jacob Ziskind Building
Lecturer: Dimitar Granthcharov
Organizer: Faculty of Mathematics and Computer Science
Abstract: TBA ...TBA

Seminar in Geometry and Topology

Date:
17
Tuesday
May
2016
Lecture / Seminar
Time: 16:15-18:00
Title: Optimal Interpolation in approximation theory, nonparametric regression and optimal design
Location: Jacob Ziskind Building
Lecturer: Boris Levit
Organizer: Faculty of Mathematics and Computer Science

Foundations of Computer Science Seminar

Date:
16
Monday
May
2016
Lecture / Seminar
Time: 14:30-16:00
Title: Sampling Correctors
Location: Jacob Ziskind Building
Lecturer: Ronitt Rubinfeld
Organizer: Faculty of Mathematics and Computer Science
Abstract: In many situations, sample data is obtained from a noisy or imperfect source. In ...In many situations, sample data is obtained from a noisy or imperfect source. In order to address such corruptions, we propose the methodology of sampling correctors. Such algorithms use structure that the distribution is purported to have, in order to allow one to make "on-the-fly" corrections to samples drawn from probability distributions. These algorithms may then be used as filters between the noisy data and the end user. We show connections between sampling correctors, distribution learning algorithms, and distribution property testing algorithms. We show that these connections can be utilized to expand the applicability of known distribution learning and property testing algorithms as well as to achieve improved algorithms for those tasks.

Foundations of Computer Science Seminar

Date:
09
Monday
May
2016
Lecture / Seminar
Time: 14:30-16:00
Title: Serving in the Dark should be done Non-Uniformly
Location: Jacob Ziskind Building
Lecturer: Ilan Cohen
Organizer: Faculty of Mathematics and Computer Science
Abstract: ...

Vision and Robotics Seminar

Date:
09
Monday
May
2016
Lecture / Seminar
Time: 14:00-16:00
Title: Visual Perception through Hyper Graphs
Location: Jacob Ziskind Building
Lecturer: Nikos Paragios
Organizer: Faculty of Mathematics and Computer Science
Abstract: Computational vision, visual computing and biomedical image analysis have made t ...Computational vision, visual computing and biomedical image analysis have made tremendous progress in the past decade. This is mostly due the development of efficient learning and inference algorithms which allow better and richer modeling of visual perception tasks. Hyper-Graph representations are among the most prominent tools to address such perception through the casting of perception as a graph optimization problem. In this talk, we briefly introduce the interest of such representations, discuss their strength and limitations, provide appropriate strategies for their inference learning and present their application to address a variety of problems of visual computing.

Algebraic Geometry and Representation Theory Seminar

Date:
05
Thursday
May
2016
Lecture / Seminar
Time: 14:00-15:15
Title: New tensor categories related to orthogonal and symplectic groups and the strange supergroup P(infinity)
Location: Jacob Ziskind Building
Lecturer: Vera Serganova
Organizer: Faculty of Mathematics and Computer Science
Abstract: We study a symmetric monoidal category of tensor representations of the ind grou ...We study a symmetric monoidal category of tensor representations of the ind group O(infinity). This category is Koszul and its Koszul dual is the category of tensor representations of the strange supergroup P(infinity). This can be used to compute Ext groups between simple objects in both categories. The above categories are missing the duality functor. It is possible to extend these categories to certain rigid tensor categories satisfying a nice universality property. In the case of O(infinity) such extension depends on a parameter t and is closely related to the Deligne’s category Rep O(t). When t is integer, this new category is a highest weight category and the action of translation functors in this category is related to the representation of gl(infinity) in the Fock space.

Geometric Functional Analysis and Probability Seminar

Date:
05
Thursday
May
2016
Lecture / Seminar
Time: 11:00-13:00
Title: One-dependent walks in hypergeometric-Dirichlet environments
Location: Jacob Ziskind Building
Lecturer: Tal Orenshtein
Organizer: Faculty of Mathematics and Computer Science
Abstract: Dirichlet environments are one of the few examples in Random Walk in Random Envi ...Dirichlet environments are one of the few examples in Random Walk in Random Environment in which some non-trivial random walk properties are fully and explicitly characterized in terms of the parameters. A key feature of the model is the so-called 'time reversal property', saying that inverting the time is resulting in the same class of models, with an explicit change of parameters. In this talk, which is based on a joint work in process with Christophe Sabot, I'll present a generalization of random walks in Dirichlet environments using hypergeometric functions having that nice feature, and discuss the question of existence of an invariant probability measure for the process on the environments from the point of view of the walker which is absolutely continuous with respect to the initial measure.

Geometric Functional Analysis and Probability Seminar

Date:
05
Thursday
May
2016
Lecture / Seminar
Time: 11:00-13:00
Title: Recurrent Random Walks on a Strip: conditions for the CLT
Location: Jacob Ziskind Building
Lecturer: Ilya Goldsheid
Organizer: Faculty of Mathematics and Computer Science
Abstract: This is joint work with Dima Dolgopyat. We prove that a recurrent random wa ... This is joint work with Dima Dolgopyat. We prove that a recurrent random walk (RW) in i.i.d. random environment (RE) on a strip which does not obey the Sinai law exhibits the Central Limit asymptotic behaviour. Moreover, there exists a collection of proper subvarieties in the space of transition probabilities such that: (a) If the RE is stationary and ergodic and the transition probabilities are concentrated on one of sub-varieties from our collection then the CLT holds

Machine Learning and Statistics Seminar

Date:
04
Wednesday
May
2016
Lecture / Seminar
Time: 11:15-12:30
Title: The Power of Initialization and a Dual View on Expressivity
Location: Jacob Ziskind Building
Lecturer: Amit Daniely
Organizer: Faculty of Mathematics and Computer Science
Abstract: We develop a general duality between neural networks and compositional kernels. ...We develop a general duality between neural networks and compositional kernels. We show that initial representations generated by common random initializations are sufficiently rich to express all functions in the dual kernel space. Hence, though the training objective is hard to optimize in the worst case, the initial weights form a good starting point for optimization. Our dual view also reveals a pragmatic and aesthetic perspective of neural networks and underscores their expressive power. Joint work with Roy Frostig and Yoram Singer

Algebraic Geometry and Representation Theory Seminar

Date:
04
Wednesday
May
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Differential algebraic groups and their applications
Location: Jacob Ziskind Building
Lecturer: Andrey Minchenko
Organizer: Faculty of Mathematics and Computer Science
Abstract: At the most basic level, differential algebraic geometry studies solution spaces ...At the most basic level, differential algebraic geometry studies solution spaces of systems of differential polynomial equations. If a matrix group is defined by a set of such equations, one arrives at the notion of a linear differential algebraic group, introduced by P. Cassidy. These groups naturally appear as Galois groups of linear differential equations with parameters. Studying linear differential algebraic groups and their representations is important for applications to finding dependencies among solutions of differential and difference equations (e.g. transcendence properties of special functions). This study makes extensive use of the representation theory of Lie algebras. Remarkably, via their Lie algebras, differential algebraic groups are related to Lie conformal algebras, defined by V. Kac. We will discuss these and other aspects of differential algebraic groups, as well as related open problems.

Mathematical Analysis and Applications Seminar

Date:
03
Tuesday
May
2016
Lecture / Seminar
Time: 11:15-12:30
Title: Spectral asymptotics for fractional Laplacian
Location: Jacob Ziskind Building
Lecturer: Victor Ivrii
Organizer: Faculty of Mathematics and Computer Science
Abstract: Consider a compact domain with the smooth boundary in the Euclidean space. Fract ...Consider a compact domain with the smooth boundary in the Euclidean space. Fractional Laplacian is defined on functions supported in this domain as a (non-integer) power of the positive Laplacian on the whole space restricted then to this domain. Such operators appear in the theory of stochastic processes. It turns out that the standard results about distribution of eigenvalues (including two-term asymptotics) remain true for fractional Laplacians. There are however some unsolved problems.

Foundations of Computer Science Seminar

Date:
02
Monday
May
2016
Lecture / Seminar
Time: 14:30-16:00
Title: MST in Log-Star Rounds of Congested Clique
Location: Jacob Ziskind Building
Lecturer: Merav Parter
Organizer: Faculty of Mathematics and Computer Science

Geometric Functional Analysis and Probability Seminar

Date:
21
Thursday
April
2016
Lecture / Seminar
Time: 11:00-13:00
Title: Large deviations for random walk in space-time random environment: averaged vs. quenched
Location: Jacob Ziskind Building
Organizer: Faculty of Mathematics and Computer Science
Abstract: I will present recent joint work with F. Rassoul-Agha (Utah) and T. Seppalainen ...I will present recent joint work with F. Rassoul-Agha (Utah) and T. Seppalainen (Madison) where we consider random walk on a hypercubic lattice of arbitrary dimension in a space-time random environment that is assumed to be temporally independent and spatially translation invariant. The large deviation principle (LDP) for the empirical velocity of the averaged walk (i.e., level-1) is simply Cramer’s theorem. We take the point of view of the particle and establish the process-level (i.e., level-3) averaged LDP for the environment Markov chain. The rate function $I_{3,a}$ is a specific relative entropy which reproduces Cramer’s rate function via the so-called contraction principle. We identify the unique minimizer of this contraction at any velocity and analyse its structure. When the environment is spatially ergodic, the level-3 quenched LDP follows from our previous work which gives a variational formula for the rate function $I_{3,q}$ involving a Donsker-Varadhan-type relative entropy $H_q$. We derive a decomposition formula for $I_{3,a}$ that expresses it as a sum of contributions from the walk (via $H_q$) and the environment. We use this formula to characterize the equality of the level-1 averaged and quenched rate functions, and conclude with several related results and open problems.

Geometric Functional Analysis and Probability Seminar

Date:
21
Thursday
April
2016
Lecture / Seminar
Time: 11:00-13:00
Title: Large deviations for random walk in space-time random environment: averaged vs. quenched
Location: Jacob Ziskind Building
Organizer: Faculty of Mathematics and Computer Science
Abstract: I will present recent joint work with F. Rassoul-Agha (Utah) and T. Seppalainen ...I will present recent joint work with F. Rassoul-Agha (Utah) and T. Seppalainen (Madison) where we consider random walk on a hypercubic lattice of arbitrary dimension in a space-time random environment that is assumed to be temporally independent and spatially translation invariant. The large deviation principle (LDP) for the empirical velocity of the averaged walk (i.e., level-1) is simply Cramer’s theorem. We take the point of view of the particle and establish the process-level (i.e., level-3) averaged LDP for the environment Markov chain. The rate function $I_{3,a}$ is a specific relative entropy which reproduces Cramer’s rate function via the so-called contraction principle. We identify the unique minimizer of this contraction at any velocity and analyse its structure. When the environment is spatially ergodic, the level-3 quenched LDP follows from our previous work which gives a variational formula for the rate function $I_{3,q}$ involving a Donsker-Varadhan-type relative entropy $H_q$. We derive a decomposition formula for $I_{3,a}$ that expresses it as a sum of contributions from the walk (via $H_q$) and the environment. We use this formula to characterize the equality of the level-1 averaged and quenched rate functions, and conclude with several related results and open problems.

Geometric Functional Analysis and Probability Seminar

Date:
21
Thursday
April
2016
Lecture / Seminar
Time: 11:00-13:00
Title: Large deviations for random walk in space-time random environment: averaged vs. quenched
Location: Jacob Ziskind Building
Lecturer: Atilla Yilmaz
Organizer: Faculty of Mathematics and Computer Science
Abstract: I will present recent joint work with F. Rassoul-Agha (Utah) and T. Seppalainen ...I will present recent joint work with F. Rassoul-Agha (Utah) and T. Seppalainen (Madison) where we consider random walk on a hypercubic lattice of arbitrary dimension in a space-time random environment that is assumed to be temporally independent and spatially translation invariant. The large deviation principle (LDP) for the empirical velocity of the averaged walk (i.e., level-1) is simply Cramer’s theorem. We take the point of view of the particle and establish the process-level (i.e., level-3) averaged LDP for the environment Markov chain. The rate function $I_{3,a}$ is a specific relative entropy which reproduces Cramer’s rate function via the so-called contraction principle. We identify the unique minimizer of this contraction at any velocity and analyse its structure. When the environment is spatially ergodic, the level-3 quenched LDP follows from our previous work which gives a variational formula for the rate function $I_{3,q}$ involving a Donsker-Varadhan-type relative entropy $H_q$. We derive a decomposition formula for $I_{3,a}$ that expresses it as a sum of contributions from the walk (via $H_q$) and the environment. We use this formula to characterize the equality of the level-1 averaged and quenched rate functions, and conclude with several related results and open problems.