conftrace_

regret bound

1926 papers

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RB

Co-occurring keywords

online learning (1777) multi-armed bandit (1098) contextual bandit (381) stochastic optimization (1060) reinforcement learning (4352) online algorithm (445) upper confidence bound (197) markov decision process (790) thompson sampling (237) online convex optimization (165)

Papers

Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation NIPS 2024
Conformal Inference for Online Prediction with Arbitrary Distribution Shifts JMLR 2024
Optimal Multiclass U-Calibration Error and Beyond NIPS 2024
Dynamic Budget Throttling in Repeated Second-Price Auctions AAAI 2024
Queueing Matching Bandits with Preference Feedback NIPS 2024
Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs NIPS 2024
Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit NIPS 2024
Improved Bandits in Many-to-One Matching Markets with Incentive Compatibility AAAI 2024
Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging AAAI 2024
Online Markov Decision Processes Configuration with Continuous Decision Space AAAI 2024
Towards Achieving Sub-linear Regret and Hard Constraint Violation in Model-free RL AISTATS 2024
Regret Bounds for Risk-sensitive Reinforcement Learning with Lipschitz Dynamic Risk Measures AISTATS 2024
On the Model-Misspecification in Reinforcement Learning AISTATS 2024
Improved Algorithm for Adversarial Linear Mixture MDPs with Bandit Feedback and Unknown Transition AISTATS 2024
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation AISTATS 2024
When Is Inductive Inference Possible? NIPS 2024
NeoRL: Efficient Exploration for Nonepisodic RL NIPS 2024
Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning NIPS 2024
Constant or Logarithmic Regret in Asynchronous Multiplayer Bandits with Limited Communication AISTATS 2024
Near-optimal Per-Action Regret Bounds for Sleeping Bandits AISTATS 2024
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits AISTATS 2024
Piecewise-Stationary Bandits with Knapsacks NIPS 2024
Safe Reinforcement Learning with Instantaneous Constraints: The Role of Aggressive Exploration AAAI 2024
Causal Q-Aggregation for CATE Model Selection AISTATS 2024
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes AAAI 2024