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stat.CO2025
Regime-Switching Langevin Monte Carlo Algorithms
Xiaoyu Wang, Yingli Wang, Lingjiong Zhu
Langevin Monte Carlo (LMC) algorithms are popular Markov Chain Monte Carlo (MCMC) methods to sample a target probability distribution, which arises in many applications in machine…
stat.ML2025
Accelerating Constrained Sampling: A Large Deviations Approach
Yingli Wang, Changwei Tu, Xiaoyu Wang +1
The problem of sampling a target probability distribution on a constrained domain arises in many applications including machine learning. For constrained sampling, various Langevin…
cs.LG2025
Non-Reversible Langevin Algorithms for Constrained Sampling
Hengrong Du, Qi Feng, Changwei Tu +2
We consider the constrained sampling problem where the goal is to sample from a target distribution on a constrained domain. We propose skew-reflected non-reversible Langevin dynam…