25 citations · 33 across the 6 of their papers we have counts for
3 papers · 1 filter
Many processors, little time: MCMC for partitions via optimal transport couplings
Tin D. Nguyen, Brian L. Trippe, Tamara Broderick
Markov chain Monte Carlo (MCMC) methods are often used in clustering since they guarantee asymptotically exact expectations in the infinite-time limit. In finite time, though, slow…
For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets
Brian L. Trippe, Hilary K. Finucane, Tamara Broderick
Hierarchical Bayesian methods enable information sharing across multiple related regression problems. While standard practice is to model regression parameters (effects) as (1) exc…
Optimal transport couplings of Gibbs samplers on partitions for unbiased estimation
Brian L. Trippe, Tin D. Nguyen, Tamara Broderick
Computational couplings of Markov chains provide a practical route to unbiased Monte Carlo estimation that can utilize parallel computation. However, these approaches depend crucia…