conftrace_

mixing time

70 papers

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Co-occurring keywords

markov chain monte carlo (725) markov chain (207) log-concave distribution (46) gibbs sampling (201) mcmc sampling (70) stochastic process (388) hamiltonian monte carlo (92) metropolis-adjusted langevin algorithm (10) log-concave sampling (13) sampling algorithm (130)

Papers

Quantifying the Effectiveness of Linear Preconditioning in Markov Chain Monte Carlo JMLR 2025
Graph-accelerated Markov Chain Monte Carlo using Approximate Samples JMLR 2025
Mixing Times and Privacy Analysis for the Projected Langevin Algorithm under a Modulus of Continuity JMLR 2025
Contraction of Markovian Operators in Orlicz Spaces and Error Bounds for Markov Chain Monte Carlo (Extended Abstract) COLT 2024
On the Computational Complexity of Metropolis-Adjusted Langevin Algorithms for Bayesian Posterior Sampling JMLR 2024
Feasible $Q$-Learning for Average Reward Reinforcement Learning AISTATS 2024
Balancing Context Length and Mixing Times for Reinforcement Learning at Scale NIPS 2024
Just Wing It: Near-Optimal Estimation of Missing Mass in a Markovian Sequence JMLR 2024
Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin Walk NIPS 2024
Sampling Polytopes with Riemannian HMC: Faster Mixing via the Lewis Weights Barrier COLT 2024
Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions NIPS 2023
Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic ICML 2023
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling COLT 2023
Sampling random graph homomorphisms and applications to network data analysis JMLR 2023
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler COLT 2023
Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators COLT 2023
A Tale of Sampling and Estimation in Discounted Reinforcement Learning AISTATS 2023
An Efficient Sampling Algorithm for Non-smooth Composite Potentials JMLR 2022
Non-asymptotic and Accurate Learning of Nonlinear Dynamical Systems JMLR 2022
Continual Learning In Environments With Polynomial Mixing Times NIPS 2022
Rapidly Mixing Multiple-try Metropolis Algorithms for Model Selection Problems NIPS 2022
Learning with little mixing NIPS 2022
Three-stage Evolution and Fast Equilibrium for SGD with Non-degerate Critical Points ICML 2022
Adapting to Mixing Time in Stochastic Optimization with Markovian Data ICML 2022
Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling JMLR 2022