This week's Statistics Seminar Speaker wil be Karthik Sridharan from the University of Pennsylvania.
Title: Online Learning: From Theory to Algorithms and Applications
Abstract: In recent years online learning (sequential prediction) has received much attention as it often produces fast and simple learning algorithms that enjoy robustness to changing or even adversarial data sources. However, despite the extensive existing literature on online learning, our theoretical understanding of the framework has been rather lacking. Most existing analyses have been case by case, and there is a lack of a general theory and methodology for designing online learning algorithms for the problem at hand. The goal of this talk is to first present a new general theory for online learning that parallels results from statistical learning theory. Next, building on this general theory, I will provide a generic recipe for deriving online learning algorithms. Finally, we shall see how the tools and techniques presented can be used for designing efficient learning algorithms for several interesting problems including online collaborative filtering, node classification in social networks, etc.
Please note: Reception at 11:45 am in front of Chair’s suite (402)