Markov Chain Monte Carlo

Sensitivity of MCMC-based analyses to small-data removal

If the conclusion of a data analysis is sensitive to dropping very few data points, that conclusion might hinge on the particular data …

Tin Nguyen, Ryan Giordano, Rachael Meager, Tamara Broderick

Using gradients to check sensitivity of MCMC-based analyses to removing data

If the conclusion of a data analysis is sensitive to dropping very few data points, that conclusion might hinge on the particular data …

Tin Nguyen, Ryan Giordano, Rachael Meager, Tamara Broderick

MIT EECS PhD thesis defense

May 7, 2024 8:00 AM — 9:00 AM Virtual

Sensitivity of MCMC analyses to data removal

Contributed talk at BAYSM:O 2023

Nov 13, 2023 1:00 PM — Nov 17, 2023 3:00 PM Virtual

Many processors, little time: MCMC for partitions via optimal transport couplings

Markov chain Monte Carlo (MCMC) methods are often used in clustering since they guarantee asymptotically exact expectations in the …

Tin Nguyen, Brian L. Trippe, Tamara Broderick

Optimal transport couplings of Gibbs samplers on partitions for unbiased estimation

Computational couplings of Markov chains provide a practical route to unbiased Monte Carlo estimation that can utilize parallel …

Brian L. Trippe, Tin Nguyen, Tamara Broderick