Previous Conferences & Workshops

Jan
29
2013

Analysis Seminar

Toeplitz Matrices and Determinants Under the Impetus of the Ising Model
Percy Deift
3:15pm|S-101

This is the second of two talks in which the speaker will discuss the development of the theory of Toeplitz matrices and determinants in response to questions arising in the analysis of the Ising model of statistical mechanics. The first talk will...

Jan
29
2013

Computer Science/Discrete Mathematics Seminar II

The Ribe Program
10:30am|S-101

A linear property of Banach spaces is called "local" if it depends on finite number of vectors and is invariant under renorming (i.e., distorting the norm by a finite factor). A famous theorem of Ribe states that local properties are invariant under...

Jan
28
2013

Members’ Seminar

Toeplitz Matrices and Determinants Under the Impetus of the Ising Model
Percy Deift
2:00pm|S-101

This is the first of two talks in which the speaker will discuss the development of the theory of Toeplitz matrices and determinants in response to questions arising in the analysis of the Ising model of statistical mechanics. The first talk will be...

Jan
28
2013

Computer Science/Discrete Mathematics Seminar I

New Independent Source Extractors with Exponential Improvement
Xin Li
11:15am|S-101

We study the problem of constructing extractors for independent weak random sources. The probabilistic method shows that such an extractor exists for two sources on n bits with min-entropy k >= 2 log n. On the other hand, explicit constructions are...

Jan
24
2013

Joint IAS/Princeton University Number Theory Seminar

Abelian varieties with maximal Galois action on their torsion points
David Zywina
4:30pm|S-101

Abstract: Associated to an abelian variety A/K is a Galois representation which describes the action of the absolute Galois group of K on the torsion points of A. In this talk, we shall describe how large the image of this representation can be (in...

Jan
23
2013

Mathematical Conversations

Provable Bounds in Machine Learning
6:00pm|Dilworth Room

Abstract: Machine learning is a vibrant field with many rich techniques. However, most approaches in the field are heuristic: we cannot prove good bounds on either their performance or their running time, except in quite limited settings. This talk...