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markov chain

207 papers

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Also known as

MC

Co-occurring keywords

markov chain monte carlo (725) mixing time (70) stochastic optimization (1060) stochastic process (388) stochastic approximation (101) bayesian inference (1907) stochastic gradient descent (1091) generative model (2892) variational inference (2069) stationary distribution (35)

Papers

Regime Switching Bandits NIPS 2021
Optimal prediction of Markov chains with and without spectral gap NIPS 2021
Learning and Testing Irreducible Markov Chains via the $k$-Cover Time ALT 2021
paht_nlp @ MEDIQA 2021: Multi-grained Query Focused Multi-Answer Summarization NAACL 2021
ChicHealth @ MEDIQA 2021: Exploring the limits of pre-trained seq2seq models for medical summarization NAACL 2021
A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence Matrices NIPS 2020
Adaptive Experimental Design with Temporal Interference: A Maximum Likelihood Approach NIPS 2020
Restless-UCB, an Efficient and Low-complexity Algorithm for Online Restless Bandits NIPS 2020
Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards NIPS 2020
Minimax Rank-$1$ Matrix Factorization AISTATS 2020
Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data IJCAI 2020
Online matrix factorization for Markovian data and applications to Network Dictionary Learning JMLR 2020
Unknown mixing times in apprenticeship and reinforcement learning UAI 2020
Probabilistic Swarm Guidance Subject to Graph Temporal Logic Specifications RSS 2020
Minimax Testing of Identity to a Reference Ergodic Markov Chain AISTATS 2020
Batch normalization provably avoids ranks collapse for randomly initialised deep networks NIPS 2020
The Autoencoding Variational Autoencoder NIPS 2020
Decentralized Langevin Dynamics for Bayesian Learning NIPS 2020
Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions AISTATS 2020
Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations AAAI 2020
Imputing typological values via phylogenetic inference EMNLP 2020
Batch Stationary Distribution Estimation ICML 2020
Stable Reinforcement Learning with Unbounded State Space L4DC 2020
Localized Learning of Robust Controllers for Networked Systems with Dynamic Topology L4DC 2020
Finite-Time Error Bounds for Biased Stochastic Approximation with Applications to Q-Learning AISTATS 2020