5 papers
Geometry and factorization of multivariate Markov chains with applications to MCMC acceleration and approximate inference
Michael C. H. Choi, Youjia Wang, Geoffrey Wolfer
This paper analyzes the factorizability and geometry of transition matrices of multivariate Markov chains. Specifically, we demonstrate that the induced chains on factors of a prod…
Group-averaged Markov chains II: tuning of group action in finite state space
Michael C. H. Choi, Ryan J. Y. Lim, Youjia Wang
We study group-averaged Markov chains obtained by augmenting a -stationary transition kernel with a group action on the state space via orbit kernels. Given a group $\mathc…
Group-averaged Markov chains: mixing improvement
Michael C. H. Choi, Youjia Wang
For Markov kernels on a general state space , we introduce a new class of averaged Markov kernels of induced by a group that acts on $\mathc…
Improving the convergence of Markov chains via permutations and projections
Michael C. H. Choi, Max Hird, Youjia Wang
This paper aims at improving the convergence to equilibrium of finite ergodic Markov chains via permutations and projections. First, we prove that a specific mixture of permuted Ma…
Information-theoretic classification of the cutoff phenomenon in Markov processes
Youjia Wang, Michael C. H. Choi
We investigate the cutoff phenomenon for Markov processes under information divergences such as -divergences and Rényi divergences. We classify most common divergences into fou…