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IDS.190 Topics in Bayesian Modeling and Computation
Probabilistic Inference and Learning with Stein’s Method
November 6, 2019 @ 4:00 pm - 5:00 pm
Lester Mackey (Microsoft Research)
37-212
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IDS.190 – Topics in Bayesian Modeling and Computation
**PLEASE NOTE ROOM CHANGE TO BUILDING 37-212 FOR THE WEEKS OF 10/30 AND 11/6**
Speaker:
Lester Mackey (Microsoft Research)
Abstract:
Stein’s method is a powerful tool from probability theory for bounding the distance between probability distributions. In this talk, I’ll describe how this tool designed to prove central limit theorems can be adapted to assess and improve the quality of practical inference procedures. I’ll highlight applications to Markov chain sampler selection, goodness-of-fit testing, variational inference, and nonconvex optimization and close with several opportunities for future work.
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**Taking IDS.190 satisfies the seminar requirement for students in MIT’s Interdisciplinary Doctoral Program in Statistics (IDPS), but formal registration is open to any graduate student who can register for MIT classes. For more information and an up-to-date schedule, please see https://stellar.mit.edu/S/course/IDS/fa19/IDS.190/
**Meetings are open to any interested researcher.
