The schedule for our tutorial (video playing in zoom) is attached below. After each main part of our tutorial, there will be a 20-minutes break for live Q & A. [PST time zone]

Learning is a predominant theme for any intelligent system, humans or machines. Moving beyond the classical paradigm of learning from past experience, e.g., supervised learning from given labels, a learner needs to actively collect exploratory feedback to learn from the unknowns, i.e., learning through exploration. This tutorial will introduce the...

In this tutorial, we will first motivate the need of exploration in machine learning algorithms and highlight its importance in many real-world problems where online sequential decision making is involved. In real-world application scenarios, considerable challenges arise in such a setting of machine learning, including sample complexity, costly and even...

This tutorial will be given by three researchers from the Department of Computer Science at the University of Virginia.

Although learning by exploration is a vital capability for modern intelligent systems and extensive research effort has been devoted, there are not too many tutorial covering the exciting developments on this direction. Prior to our tutorial, we only found two related tutorials; and we would like to share them with...