regret bound

Horizon-Free Regret for Linear Markov Decision Processes ICLR 2024 Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs ICLR 2024 How Does Variance Shape the Regret in Contextual Bandits? NeurIPS 2024 Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition AISTATS 2024 Improved Algorithms for Contextual Dynamic Pricing NeurIPS 2024 Improved Analysis for Bandit Learning in Matching Markets NeurIPS 2024 Improved Bandits in Many-to-One Matching Markets with Incentive Compatibility AAAI 2024 Improved Bayes Regret Bounds for Multi-Task Hierarchical Bayesian Bandit Algorithms NeurIPS 2024 Improved learning rates in multi-unit uniform price auctions NeurIPS 2024 Improved Regret Bounds for Non-Convex Online-Within-Online Meta Learning ICLR 2024 Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion AISTATS 2024 Improved Regret for Bandit Convex Optimization with Delayed Feedback NeurIPS 2024 Improved Regret of Linear Ensemble Sampling NeurIPS 2024 Improving Adaptive Online Learning Using Refined Discretization ALT 2024 Information Capacity Regret Bounds for Bandits with Mediator Feedback JMLR 2024 Learnability Gaps of Strategic Classification COLT 2024 Learning-Based Algorithms for Graph Searching Problems AISTATS 2024 Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach JMLR 2024 Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm NeurIPS 2024 Learning Optimal Contracts: How to Exploit Small Action Spaces ICLR 2024 Learning Thresholds with Latent Values and Censored Feedback ICLR 2024 Learning to Price Homogeneous Data NeurIPS 2024 Leveraging (Biased) Information: Multi-armed Bandits with Offline Data ICML 2024 Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging AAAI 2024 Linear Causal Bandits: Unknown Graph and Soft Interventions NeurIPS 2024