Time+Place: Tuesday 04/11/2014 14:30 Room 337-8 Taub Bld.
Title: Robust Probabilistic Inference
Speaker: Yishay Mansour - Colloquium Lecture http://www.math.tau.ac.il/~mansour/
Affiliation: School of Computer Science, Tel-Aviv University
Host: Erez Petrank


Probabilistic Inference is the task of given a certain set of 
observations, to deduce the probability of various outcomes. This is a 
very basic task both in statistics and in machine learning. Robust 
probabilistic inference is an extension of probabilistic inference, 
where some of the observations are adversarially corrupted. Examples of 
where such a model may be relevant are spam detection, where spammers 
try adversarially to fool the spam detectors, or failure detection and 
correction, where the failure can be modeled as a ''worse case'' 
failure. The framework can be also used to model selection 
between a few alternative models  that possibly generate the data. 
Technically, we model robust probabilistic inference as a zero-sum game 
between an adversary, who can select a modification rule, and a 
predictor, who wants to accurately predict the state of nature. Our main 
result is an efficient near optimal algorithm for the robust 
probabilistic inference problem. More specifically, given a black-box 
access to a Bayesian inference in the classic (adversary-free) setting, 
our near optimal policy runs in polynomial time in the number of 
observations and the number of possible modification rules.

This is a joint work with Aviad Rubinstein and Moshe Tennenholtz

Prof. Yishay Mansour is a Professor of Computer Science at Tel-Aviv 
University. He received his PhD from MIT in 1990, following it he was a 
postdoctoral fellow in Harvard and a Research Staff Member in IBM T. J. 
Watson Research Center. Prof. Mansour joined Microsoft Research in 
Israel in 2014. Before that he held visiting positions with Microsoft, 
Bell Labs, AT&T research Labs, IBM Research, and Google Research. He has 
mentored start-ups, e.g., Riverhead, which was acquired by Cisco, 
Ghoonet and Verix.

Prof. Mansour has published numerous journal and proceeding papers in 
various areas of computer science with special emphasis on communication 
networks, machine learning, and algorithmic game theory, and has 
supervised over a dozen graduate students in those areas. Prof. Mansour 
is currently an associate editor in a multiple distinguished journals 
and has been on numerous conference program committees. He was the 
program chair of  COLT (1998) and serves on the COLT steering committee.

Deserts will be served from 14:15
Lecture starts at 14:30