3 papers
cs.DS2025
Markov Chains Approximate Message Passing
Amit Rajaraman, David X. Wu
Markov chain Monte Carlo algorithms have long been observed to obtain near-optimal performance in various Bayesian inference settings. However, developing a supporting theory that…
cs.DS2025
Locally Stationary Distributions: A Framework for Analyzing Slow-Mixing Markov Chains
Kuikui Liu, Sidhanth Mohanty, Prasad Raghavendra +2
Many natural Markov chains fail to mix to their stationary distribution in polynomially many steps. Often, this slow mixing is inevitable since it is computationally intractable to…
math.PR2024
Weak Poincaré Inequalities, Simulated Annealing, and Sampling from Spherical Spin Glasses
Brice Huang, Sidhanth Mohanty, Amit Rajaraman +1
There has been a recent surge of powerful tools to show rapid mixing of Markov chains, via functional inequalities such as Poincaré inequalities. In many situations, Markov chains…