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Exploration-Exploitation

203 papers

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Papers

Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards NeurIPS 2020 From Finite to Countable-Armed Bandits NeurIPS 2020 Generative Exploration and Exploitation AAAI 2020 Incentivized Exploration for Multi-Armed Bandits under Reward Drift AAAI 2020 Information Directed Sampling for Linear Partial Monitoring COLT 2020 Online Evaluation of Audiences for Targeted Advertising via Bandit Experiments AAAI 2020 Optimal Best-arm Identification in Linear Bandits NeurIPS 2020 Regret Minimisation in Multi-Armed Bandits Using Bounded Arm Memory AAAI 2020 Restless-UCB, an Efficient and Low-complexity Algorithm for Online Restless Bandits NeurIPS 2020 Safe Linear Stochastic Bandits AAAI 2020 Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces NeurIPS 2020 Taking a hint: How to leverage loss predictors in contextual bandits? COLT 2020 Thompson Sampling via Local Uncertainty ICML 2020 Tsallis-INF for Decoupled Exploration and Exploitation in Multi-armed Bandits COLT 2020 Are sample means in multi-armed bandits positively or negatively biased? NeurIPS 2019 Balanced Linear Contextual Bandits AAAI 2019 Blocking Bandits NeurIPS 2019 Contextual Bandits with Cross-Learning NeurIPS 2019 Dueling Bandits with Qualitative Feedback AAAI 2019 Dynamic Learning of Sequential Choice Bandit Problem under Marketing Fatigue AAAI 2019 Epsilon-Best-Arm Identification in Pay-Per-Reward Multi-Armed Bandits NeurIPS 2019 Explicit Explore-Exploit Algorithms in Continuous State Spaces NeurIPS 2019 Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs NeurIPS 2019 Hindsight Credit Assignment NeurIPS 2019 Information-Theoretic Confidence Bounds for Reinforcement Learning NeurIPS 2019