stationary distribution

Perfect Sampling from Pairwise Comparisons NeurIPS 2022 Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning ICML 2022 Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent ICML 2021 Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders AISTATS 2021 On Riemannian Stochastic Approximation Schemes with Fixed Step-Size AISTATS 2021 OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation ICML 2021 Reward is enough for convex MDPs NeurIPS 2021 A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPs NeurIPS 2020 Batch Stationary Distribution Estimation ICML 2020 Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning ICLR 2020 GenDICE: Generalized Offline Estimation of Stationary Values ICLR 2020 GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values ICML 2020 Infinite-horizon Off-Policy Policy Evaluation with Multiple Behavior Policies ICLR 2020 Off-Policy Evaluation via the Regularized Lagrangian NeurIPS 2020 Steady-State Policy Synthesis in Multichain Markov Decision Processes IJCAI 2020 DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections NeurIPS 2019 Estimating the Mixing Time of Ergodic Markov Chains COLT 2019 Off-Policy Policy Gradient with Stationary Distribution Correction UAI 2019 Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation NeurIPS 2018 Entropy Rate Estimation for Markov Chains with Large State Space NeurIPS 2018 Consistent On-Line Off-Policy Evaluation ICML 2017 Fast and Accurate Inference of Plackett–Luce Models NeurIPS 2015 Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter Sets NeurIPS 2015 Reflection, Refraction, and Hamiltonian Monte Carlo NeurIPS 2015 Computing the Stationary Distribution Locally NeurIPS 2013