BIRS Workshop Lecture Videos

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BIRS Workshop Lecture Videos

Recent Developments of Iterative Monte Carlo Methods for Big Data Analysis (Faming Liang & Chuanhai Liu) Liang, Faming


Iterative Monte Carlo methods, such as MCMC, stochastic approximation, and EM, have proven to be very powerful tools for statistical data analysis. However, their computer- intensive nature, which typically require a large number of iterations and a complete scan of the full dataset for each iteration, precludes their use for big data analysis. We will provide an overview of the recent developments of iterative Monte Carlo methods for big data analysis. The portion by Liang will focus on the developments of the MCMC and stochastic approximation methods, and that by Liu will focus on the developments of the EM method.

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