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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…