Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'

Category 'Best Course for New Knowledge and Skills'

Delivered at:: Big Data and Information Retrieval School

Course type:: Compulsory course

When:: 1 year, 2, 3 module

Instructors

Levin, Ilya

Samsonov, Sergey

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Abstract

The course is an introduction to the theory of Markov chains, an area of modern probability theory widely used in applications. In this course, we will start from the theory of finite state space Markov chains and continue with the general case of Markov chains with arbitrary state space. We will cover various ergodicity results for Markov kernels and relations between them, central limit theorem for Markov chains, and applications of Markov chains. In terms of applications, we will consider the Markov Chain Monte Carlo methods and study some most classical examples of algorithms of this family.

Master’s Programme 'Math of Machine Learning'

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Markov Chains

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Abstract