Markov Chain Mixing Times and Applications II
Ivona Bezakova, Rochester Institute of Technology and Nayantara Bhatnagar, University of Delaware
Calvin Lab Auditorium
This mini-course will present the fundamentals of analysis of convergence rates of discrete time Markov chains, and applications from statistical physics and combinatorics. It will start with an introduction to Markov chains and their properties, and relation between sampling and counting. Then it will discuss techniques for bounding the mixing time: The second session will focus on coupling and the third session on canonical paths and related concepts.
The first session of this mini course will take place on Monday, January 25 from 1:30 pm – 2:30 pm; the third session of this mini course will take place on Wednesday, January 27 from 3:00 pm – 4:00 pm.
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Markov Chain Mixing Times and Applications II | 6.72 MB |