14 citations · 37 across the 19 of their papers we have counts for
4 papers · 1 filter
Bounds on Lifting Continuous Markov Chains to Speed Up Mixing
Kavita Ramanan, Aaron Smith
It is often possible to speed up the mixing of a Markov chain on a state space by \textit{lifting}, that is, running a more efficient Markov ch…
Parallel Markov Chain Monte Carlo via Spectral Clustering
Guillaume W. Basse, Natesh S. Pillai, Aaron Smith
As it has become common to use many computer cores in routine applications, finding good ways to parallelize popular algorithms has become increasingly important. In this paper, we…
On the Mixing Time of Kac's Walk and Other High-Dimensional Gibbs Samplers with Constraints
Natesh S. Pillai, Aaron Smith
Determining the total variation mixing time of Kac's random walk on the special orthogonal group has been a long-standing open problem. In this paper, we construct…
MCMC for Imbalanced Categorical Data
James E. Johndrow, Aaron Smith, Natesh Pillai +1
Many modern applications collect highly imbalanced categorical data, with some categories relatively rare. Bayesian hierarchical models combat data sparsity by borrowing informatio…