Multi-Armed Bandits

Learning to Price Homogeneous Data NeurIPS 2024 Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances ICLR 2024 Linear bandits with polylogarithmic minimax regret COLT 2024 Linear Causal Bandits: Unknown Graph and Soft Interventions NeurIPS 2024 Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit NeurIPS 2024 Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning NeurIPS 2024 Low-rank Matrix Bandits with Heavy-tailed Rewards UAI 2024 Materials Discovery using Max K-Armed Bandit JMLR 2024 Maximizing the Success Probability of Policy Allocations in Online Systems AAAI 2024 Meta Learning in Bandits within shared affine Subspaces AISTATS 2024 Mode Estimation with Partial Feedback COLT 2024 Multi-Agent Bandit Learning through Heterogeneous Action Erasure Channels AISTATS 2024 Multi-armed bandits with guaranteed revenue per arm AISTATS 2024 Multiobjective Lipschitz Bandits under Lexicographic Ordering AAAI 2024 Mutli-Armed Bandits with Network Interference NeurIPS 2024 Navigating Uncertainty in Epidemic Contexts with Reinforcement Learning AAAI 2024 Near Optimal Adversarial Attacks on Stochastic Bandits and Defenses with Smoothed Responses AISTATS 2024 Near-optimal Per-Action Regret Bounds for Sleeping Bandits AISTATS 2024 Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits AISTATS 2024 No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints AISTATS 2024 No-Regret Bandit Exploration based on Soft Tree Ensemble Model NeurIPS 2024 No-Regret Learning for Fair Multi-Agent Social Welfare Optimization NeurIPS 2024 No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting NeurIPS 2024 On Differentially Private Federated Linear Contextual Bandits ICLR 2024 One Shot Inverse Reinforcement Learning for Stochastic Linear Bandits UAI 2024