Recent Advancements in Multi-armed Bandit: from Clinical Trials to Sponsored Search Auctions
Alessandro Lazaric
INRIA
DEI - Seminar Room
April 13th, 2012
2.30 - 3.30 p.m.
Abstract:
The multi-armed bandit model effectively describes a wide range of online decision-making problems such as identifying the most effective treatment in clinical trial, finding the advertisement which is more likely to be clicked in a web advertising platform, discovering the shortest path in a graph, and so on. In this talk, we will cover some recent advancements in the multi-armed bandit extending the standard setting to novel problems such as the best-arm identification (eg, returning the best treatment after a finite number of patients), active bandit setting (eg, accurate estimation of the reliability of different production lines), and the application of bandits to strategic settings (eg, web advertising).
Contacts:
Nicola Gatti
Research area:
Artificial intelligence, robotics and computer vision
