# Difference between revisions of "Probability Seminar"

(→Thursday, October 19, 2017 Varun Jog, UW-Madison ECE and Grainger Institute) |
(→Friday, November 17, 2017, 1pm Karl Leichty DePaul University) |
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== Thursday, November 9, 2017, Chen Jia, University of Texas at Dallas == | == Thursday, November 9, 2017, Chen Jia, University of Texas at Dallas == | ||

− | == <span style="color:red"> Friday,</span> November 17, 2017, <span style="color:red"> 1pm </span> [http://math.depaul.edu/kliechty/ Karl Leichty] [https://csh.depaul.edu/academics/mathematical-sciences/Pages/default.aspx DePaul University] == | + | == <span style="color:red"> Friday,</span> November 17, 2017, <span style="color:red"> 1pm, Van Vleck B223 </span> [http://math.depaul.edu/kliechty/ Karl Leichty] [https://csh.depaul.edu/academics/mathematical-sciences/Pages/default.aspx DePaul University] == |

## Revision as of 09:50, 12 October 2017

# Fall 2017

**Thursdays in 901 Van Vleck Hall at 2:25 PM**, unless otherwise noted.
**We usually end for questions at 3:15 PM.**

If you would like to sign up for the email list to receive seminar announcements then please send an email to join-probsem@lists.wisc.edu.

## Thursday, September 14, 2017, Brian Rider Temple University

**A universality result for the random matrix hard edge**

The hard edge refers to the distribution of the smallest singular value for certain ensembles of random matrices, or, and what is the same, that of the minimal point of a logarithmic gas constrained to the positive half line. For any "inverse temperature" and “quadratic" potential the possible limit laws (as the dimension, or number of particles, tends to infinity) was characterized by Jose Ramirez and myself in terms of the spectrum of a (random) diffusion generator. Here we show this picture persists for more general convex polynomial potentials. Joint work with Patrick Waters.

## Thursday, October 19, 2017 Varun Jog, UW-Madison ECE and Grainger Institute

Title: **Teaching and learning in uncertainty**

Abstract: We investigate a simple model for social learning with two characters: a teacher and a student. The teacher's goal is to teach the student the state of the world [math]\Theta[/math], however, the teacher herself is not certain about [math]\Theta[/math] and needs to simultaneously learn it and teach it. We examine several natural strategies the teacher may employ to make the student learn as fast as possible. Our primary technical contribution is analyzing the exact learning rates for these strategies by studying the large deviation properties of the sign of a transient random walk on [math]\mathbb Z[/math].

## Thursday, October 26, 2017, Konstantin Matetski Toronto

## Thursday, November 2, 2017, TBA

## Thursday, November 9, 2017, Chen Jia, University of Texas at Dallas

## Friday, November 17, 2017, 1pm, Van Vleck B223 Karl Leichty DePaul University

** Please note the unusual day and time **