markov chain

Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards NeurIPS 2020 Finite-Time Error Bounds for Biased Stochastic Approximation with Applications to Q-Learning AISTATS 2020 GenDICE: Generalized Offline Estimation of Stationary Values ICLR 2020 Geometric Insights into the Convergence of Nonlinear TD Learning ICLR 2020 Imputing typological values via phylogenetic inference EMNLP 2020 Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations AAAI 2020 Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data IJCAI 2020 Localized Learning of Robust Controllers for Networked Systems with Dynamic Topology L4DC 2020 Minimax Rank-$1$ Matrix Factorization AISTATS 2020 Minimax Testing of Identity to a Reference Ergodic Markov Chain AISTATS 2020 Online matrix factorization for Markovian data and applications to Network Dictionary Learning JMLR 2020 PCMC-Net: Feature-based Pairwise Choice Markov Chains ICLR 2020 Probabilistic Swarm Guidance Subject to Graph Temporal Logic Specifications RSS 2020 Restless-UCB, an Efficient and Low-complexity Algorithm for Online Restless Bandits NeurIPS 2020 Robust Gradient-Based Markov Subsampling AAAI 2020 Stable Reinforcement Learning with Unbounded State Space L4DC 2020 Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions AISTATS 2020 The Autoencoding Variational Autoencoder NeurIPS 2020 Unknown mixing times in apprenticeship and reinforcement learning UAI 2020 Accelerate CNN via Recursive Bayesian Pruning ICCV 2019 Discrete Object Generation with Reversible Inductive Construction NeurIPS 2019 Efficient Diversified Mini-Batch Selection using Variable High-layer Features ACML 2019 Estimating the Mixing Time of Ergodic Markov Chains COLT 2019 Fast Algorithm for Generalized Multinomial Models with Ranking Data ICML 2019 Generation of Policy-Level Explanations for Reinforcement Learning AAAI 2019