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Exploration-Exploitation

154 directly classified papers

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Papers

Recurrent Submodular Welfare and Matroid Blocking Semi-Bandits NIPS 2021
Provable Model-based Nonlinear Bandit and Reinforcement Learning: Shelve Optimism, Embrace Virtual Curvature NIPS 2021
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security AAAI 2021
Meta-Learning Effective Exploration Strategies for Contextual Bandits AAAI 2021
Stochastic Bandits with Graph Feedback in Non-Stationary Environments AAAI 2021
CORe: Capitalizing On Rewards in Bandit Exploration UAI 2021
Learning from eXtreme Bandit Feedback AAAI 2021
Combinatorial Pure Exploration with Bottleneck Reward Function NIPS 2021
Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits AAAI 2021
The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle NIPS 2021
Reinforcement Learning with Trajectory Feedback AAAI 2021
Bandit Phase Retrieval NIPS 2021
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs NIPS 2021
Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization NIPS 2021
Bandits with Knapsacks beyond the Worst Case NIPS 2021
Safe Linear Stochastic Bandits AAAI 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 NIPS 2020
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces NIPS 2020
Incentivized Exploration for Multi-Armed Bandits under Reward Drift AAAI 2020
Choice Bandits NIPS 2020
Generative Exploration and Exploitation AAAI 2020
Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards NIPS 2020
From Finite to Countable-Armed Bandits NIPS 2020
Thompson Sampling via Local Uncertainty ICML 2020