Ito Processes, Correlated Sampling and Applications

We will see the basics of Ito calculus and Girsanov’s change of measure formula. Following Lehec, one can use these tools to construct a “minimum energy” coupling (Follmer’s drift) between the Gaussian measure and any other absolutely continuous probability measure on Rn. The log-Sobolev inequality and Talagrand’s Entropy-Transport inequality then fall out effortlessly. The same philosophy will then be applied to discrete spaces like the hypercube, the symmetric group (with transpositions as generators), and general discrete Markov chains. (Joint work with Ronen Eldan).

Speaker Details

James Lee is an Associate Professor at the Department of Computer Science and Engineering, University of Washington. He received a PhD in CS from Berkeley, After a postdoc in Avi Wigderson’s group at the Institute for Advanced Study in Princeton he joined UW. More details, James’ papers and his non-blog can be found at http://www.cs.washington.edu/homes/jrl/

Series:
Microsoft Research Talks
Date:
Speakers:
James R. Lee
Affiliation:
University of Washington

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      Jeff Running

Series: Microsoft Research Talks