conftrace_

regret bound

1926 papers

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Also known as

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

Nearly Optimal Competitive Ratio for Online Allocation Problems with Two-sided Resource Constraints and Finite Requests ICML 2023
Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits ICML 2023
Bandit Task Assignment with Unknown Processing Time NIPS 2023
Robust Lipschitz Bandits to Adversarial Corruptions NIPS 2023
Revisiting Weighted Strategy for Non-stationary Parametric Bandits AISTATS 2023
Combinatorial Neural Bandits ICML 2023
Finite-Time Logarithmic Bayes Regret Upper Bounds NIPS 2023
Risk-aware linear bandits with convex loss AISTATS 2023
Online Clustering of Bandits with Misspecified User Models NIPS 2023
Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning NIPS 2023
Instance-Optimality in Interactive Decision Making: Toward a Non-Asymptotic Theory COLT 2023
Dynamical Linear Bandits ICML 2023
Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework NIPS 2023
Model-Free Reinforcement Learning with the Decision-Estimation Coefficient NIPS 2023
Contextual Gaussian Process Bandits with Neural Networks NIPS 2023
Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits AISTATS 2023
Learning and Collusion in Multi-unit Auctions NIPS 2023
Provably Safe Reinforcement Learning with Step-wise Violation Constraints NIPS 2023
Bandits with Knapsacks: Advice on Time-Varying Demands ICML 2023
A PDE approach for regret bounds under partial monitoring JMLR 2023
Provable Hierarchy-Based Meta-Reinforcement Learning AISTATS 2023
Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits NIPS 2023
Uniformly Conservative Exploration in Reinforcement Learning AISTATS 2023
Non-Stationary Bandits with Auto-Regressive Temporal Dependency NIPS 2023
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards ICML 2023