University of Massachusetts Amherst

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New and Old Concentration Inequalities - Philip Thomas

Machine Learning and Friends Lunch
March 22, 12:00pm
Computer Science Building, Room 150/151

Abstract:

In this talk I will review Hoeffding's inequality before presenting some other old and new concentration inequalities, including a strict improvement on Hoeffding's inequality (for identically distributed random variables) and a concentration inequality for conditional value at risk (CVaR).

 

Bio:

I study a branch of artificial intelligence (AI) called reinforcement learning (RL). I am currently co-directing the Autonomous Learning Lab (ALL) at UMass Amherst with Sridhar Mahadevan. Before that I worked as a postdoc for Emma Brunskill at CMU. I completed my Ph.D. in computer science at UMass Amherst in 2015, where Andrew Barto was my adviser. I completed my B.S. and M.S. in computer science at CWRU in 2008 and 2009, where Michael Branicky was my adviser. Before that, in high school, I was introduced to computer science and mentored by David Kosbie.