MCMC
Title: The Magic of MCMC and Statistics: A Live Performance
Abstract: Markov chain Monte Carlo (MCMC) methods, originated in computational physics more than half a century ago, have had magical impact in quantitative scientific investigations. This is mainly due to their ability to simulate from very complex distributions needed by all kinds of statistical models, from bioinformatics to financial engineering to astronomy. This talk provides an introductory tutorial of the two most frequently used MCMC algorithms: the Gibbs sampler and the Metropolis-Hastings algorithm. Using simple yet... Read more about MCMC: Xiao-Li Meng
Title: Statistical Mechanics on Sparse Random Graphs: Mathematical Perspective
Abstract: Theoretical models of disordered materials lead to challenging mathematical problems with applications to random combinatorial problems and coding theory. The underlying structure is that of many discrete variables that are strongly interacting according to a mean field model determined by a random sparse graph. Focusing on random finite graphs that converge locally to trees we review recent progress in validating the `cavity prediction for the limiting free energy per vertex and the approximation of... Read more about CMSA Talk: Amir Dembo
Alexander Franks
Bayesian Inference with Non-Ignorable Missing Data
Qian Lin
On Consistency and Sparsity for Sliced Inverse Regression in High Dimensions
