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A Gentle Introduction to Markov chain Monte Carlo

Prof. Dootika Vats, (IIT Kanpur)
Prof. Dootika Vats, (IIT Kanpur)
When Sep 28, 2021
from 04:00 PM to 05:00 PM
Where zoom meet
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Abstract: Monte Carlo sampling techniques are often either inefficient or practically impossible when sampling from high-dimensional and complicated distributions. In such situations, Markov chain Monte Carlo techniques are popularly employed. However, owing to the introduction of correlated sampling, special care must be taken to ensure ergodicity of the underlying process. I will motivate the need for Markov chain Monte Carlo (MCMC) and explain popular algorithms that yield theoretically well-behaved Markov chains. The popular Metropolis-Hastings algorithm will be given special attention and some variants of the algorithm will be discussed. Further, I will touch upon the practical difficulties of implementing MCMC algorithms in the modern world of big data.

Youtube link to the recording

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