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thompson sampling

237 papers

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TS

Co-occurring keywords

regret bound (1926) multi-armed bandit (1098) bayesian optimization (624) online learning (1777) contextual bandit (381) bayesian inference (1907) upper confidence bound (197) bayesian regret (33) reinforcement learning (4352) posterior distribution (259)

Papers

Thompson Sampling for the MNL-Bandit COLT 2017
Thompson Sampling for Linear-Quadratic Control Problems AISTATS 2017
Context Attentive Bandits: Contextual Bandit with Restricted Context IJCAI 2017
Linear Thompson Sampling Revisited AISTATS 2017
Scalable Generalized Linear Bandits: Online Computation and Hashing NIPS 2017
Learning Unknown Markov Decision Processes: A Thompson Sampling Approach NIPS 2017
Optimistic posterior sampling for reinforcement learning: worst-case regret bounds NIPS 2017
Efficient Benchmarking of NLP APIs using Multi-armed Bandits EACL 2017
Horde of Bandits using Gaussian Markov Random Fields AISTATS 2017
Ensemble Sampling NIPS 2017
On Thompson Sampling and Asymptotic Optimality IJCAI 2017
The End of Optimism? An Asymptotic Analysis of Finite-Armed Linear Bandits AISTATS 2017
Optimistic Gittins Indices NIPS 2016
Double Thompson Sampling for Dueling Bandits NIPS 2016
An Information-Theoretic Analysis of Thompson Sampling JMLR 2016
Simple Bayesian Algorithms for Best Arm Identification COLT 2016
Bandit Convex Optimization: \sqrtT Regret in One Dimension COLT 2015
Reactive bandits with attitude AISTATS 2015
Thompson Sampling for Learning Parameterized Markov Decision Processes COLT 2015
Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays ICML 2015
Efficient Thompson Sampling for Online Matrix-Factorization Recommendation NIPS 2015
Efficient Learning in Large-Scale Combinatorial Semi-Bandits ICML 2015
Sensor Selection for Crowdsensing Dynamical Systems AISTATS 2015
Thompson Sampling for Complex Online Problems ICML 2014
Cover Tree Bayesian Reinforcement Learning JMLR 2014