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Statistics Colloquium by Ian Shen ’19

Wed, April 17th, 2019
1:10 pm
- 1:50 pm

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The Tightening Boundary: Improving the Speed of MCMC Algorithms With Variational Methods by Ian Shen ’19, Statistics Colloquium, Wednesday, April 17, 1:10 – 1:50 pm, Stetson Court Classroom 105

Abstract:  In Bayesian inference, a precise posterior distribution can be difficult to determine in practice. While the Markov Chain Monte Carlo (MCMC) resampling algorithm is an excellent way of eventually approaching a correct posterior, it is often long and computationally intensive. This talk will introduce the concept of variational inference and combine it with MCMC methods in order to generate a more rapidly converging posterior approximation.

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