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math.ST2026
Fast Mixing of Data Augmentation Algorithms: Bayesian Probit, Logit, and Lasso Regression
Holden Lee, Kexin Zhang
We propose using a modified conductance-based method to study the mixing time of an important class of two-block Gibbs samplers, the data augmentation (DA) algorithm. %, which is o…
math.ST2026
Convergence Bounds for Sequential Monte Carlo on Multimodal Distributions using Soft Decomposition
Holden Lee, Matheau Santana-Gijzen
We prove bounds on the variance of a function under the empirical measure of the samples obtained by the Sequential Monte Carlo (SMC) algorithm, with time complexity depending…