Speaker |
Remi Munos |
|---|---|
Affiliation |
INRIA Lille |
Date |
Friday, 12 September 2014 |
Time |
13:00-14:00 |
Location |
Zoom |
Link |
Roberts G08 (Sir David Davies LT) |
Event series |
DeepMind/ELLIS CSML Seminar Series |
Abstract |
Abstract: I will describe two principles considered in multi-armed bandits, namely the optimistic principle and Thompson sampling, and illustrate how they extend to structured bandit settings, such as in linear bandits and bandits in graphs. Bio: Remi Munos received his PhD in 1997 in Cognitive Science from EHESS, France, and did a postdoc at CMU from 1998-2000. Then he was Assistant Professor in the department of Applied Mathematics at Ecole Polytechnique. In 2006 he joined the French public research institute INRIA as a Senior Researcher and co-leaded the project-team SequeL (Sequential Learning) which now gather approximately 25 people. His research interests cover several fields of Statistical Learning including Reinforcement Learning, Optimization, and Bandit Theory. Slides for the talk: PDF |
Biography |