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

Rapidly Mixing Multiple-try Metropolis Algorithms for Model Selection Problems NIPS 2022
Learning with little mixing NIPS 2022
Structured Logconcave Sampling with a Restricted Gaussian Oracle COLT 2021
High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm JMLR 2021
Mixing Time of Metropolis-Hastings for Bayesian Community Detection JMLR 2021
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions NIPS 2021
Towards Tight Bounds on the Sample Complexity of Average-reward MDPs ICML 2021
Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm COLT 2021
Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds NIPS 2021
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms NIPS 2020
Langevin Monte Carlo without smoothness AISTATS 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo COLT 2020
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients JMLR 2020
Mixing Time Estimation in Ergodic Markov Chains from a Single Trajectory with Contraction Methods ALT 2020
Unknown mixing times in apprenticeship and reinforcement learning UAI 2020
Log-concave sampling: Metropolis-Hastings algorithms are fast JMLR 2019
Random Walks on Hypergraphs with Edge-Dependent Vertex Weights ICML 2019
Mixing of Hamiltonian Monte Carlo on strongly log-concave distributions 2: Numerical integrators AISTATS 2019
Large Scale Markov Decision Processes with Changing Rewards NIPS 2019
Estimating the Mixing Time of Ergodic Markov Chains COLT 2019
Layerwise Systematic Scan: Deep Boltzmann Machines and Beyond AISTATS 2018
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo NIPS 2018
Exponentiated Strongly Rayleigh Distributions NIPS 2018
Fast MCMC Sampling Algorithms on Polytopes JMLR 2018
Log-concave sampling: Metropolis-Hastings algorithms are fast! COLT 2018