Adversarial bandit problems: the power of randomization
published: Nov. 16, 2010, recorded: September 2010, views: 5991
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
In this tutorial we discuss sequential prediction problems in which the forecaster has limited information about the past outcomes of the sequence. We concentrate on the so-called "adversarial" framework in which no probabilistic is available for the sequence. We describe various models of limited feedback and pay special attention to the so-called "multi-armed bandit" problem. We discuss various randomized prediction methods and analyze their behavior.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !