3 papers
math.ST2026
Cost Comparisons for Random and Deterministic Scans in Component-Wise Markov Chains
Youngwoo Kwon
Gibbs samplers, and more generally component-wise Markov chain Monte Carlo algorithms such as Metropolis-within-Gibbs, can be implemented using either random-scan or deterministic-…
math.ST2026
Solidarity of Spectral Gaps for Component-Wise Markov Chains
Youngwoo Kwon, Galin Jones, Qian Qin
Deterministic-scan and random-scan component-wise Markov chain Monte Carlo algorithms, such as Gibbs samplers and conditional Metropolis-Hastings, are popular approaches for sampli…
cs.LG2024
A phase transition in sampling from Restricted Boltzmann Machines
Youngwoo Kwon, Qian Qin, Guanyang Wang +1
Restricted Boltzmann Machines are a class of undirected graphical models that play a key role in deep learning and unsupervised learning. In this study, we prove a phase transition…