
Seminar will be exclusively online (no inroom presentation)  CS Colloquium: Vatsal Sharan (Stanford)  Modern Perspectives on Classical Learning Problems: Role of Memory and Data Amplification
Mon, Apr 06, 2020 @ 11:00 AM  12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Vatsal Sharan, Stanford University
Talk Title: Modern Perspectives on Classical Learning Problems: Role of Memory and Data Amplification
Series: CS Colloquium
Abstract: This talk will discuss statistical and computation requirementsand how they interactfor three learning setups. In the first part, we inspect the role of memory in learning. We study how the total memory available to a learning algorithm affects the amount of data needed for learning (or optimization), beginning by considering the fundamental problem of linear regression. Next, we examine the role of longterm memory vs. shortterm memory for the task of predicting the next observation in a sequence given the past observations. Finally, we explore the statistical requirements for the task of manufacturing more datanamely how to generate a larger set of samples from an unknown distribution. Can "amplifying" a dataset be easier than learning?
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Vatsal Sharan is a Ph.D. student at Stanford, advised by Greg Valiant. He is a part of the Theory group and the Statistical Machine Learning group, and his primary interests are in the theory and practice of machine learning.
Host: Shaddin Dughmi
Location: Seminar will be exclusively online (no inroom presentation)
Audiences: Everyone Is Invited
Contact: Assistant to CS chair