Learning through Exploration
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.
This tutorial is about learning through exploration. The goal is to learn how to make decisions in partial feedback settings where an agent repeatedly observes some information, chooses an action, and then learns how this action paid off (but doesn't get to see how other actions would have paid off). We plan to cover all aspects of this general problem: learning, evaluation, limitations of ability to learn in this setting, and the relationship to traditional supervised learning.
Download slides: kdd2010_beygelzimer_langford_lte.pdf (1.1 MB)
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !