BEGIN:VCALENDAR METHOD:PUBLISH PRODID:-//Apple Computer\, Inc//iCal 1.0//EN X-WR-CALNAME;VALUE=TEXT:USC VERSION:2.0 BEGIN:VEVENT DESCRIPTION: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 requirements---and how they interact---for 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 long-term memory vs. short-term 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 data---namely how to generate a larger set of samples from an unknown distribution. Can "amplifying" a dataset be easier than learning?\n \n 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 SEQUENCE:5 DTSTART:20200406T110000 LOCATION: Seminar will be exclusively online (no in-room presentation) DTSTAMP:20200406T110000 SUMMARY:Seminar will be exclusively online (no in-room presentation) - CS Colloquium: Vatsal Sharan (Stanford) - Modern Perspectives on Classical Learning Problems: Role of Memory and Data Amplification UID:EC9439B1-FF65-11D6-9973-003065F99D04 DTEND:20200406T120000 END:VEVENT END:VCALENDAR