conftrace_

linear bandit

124 papers

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Co-occurring keywords

regret bound (1926) multi-armed bandit (1098) online learning (1777) contextual bandit (381) stochastic optimization (1060) sample complexity (1169) thompson sampling (237) online algorithm (445) stochastic bandit (98) pure exploration (50)

Papers

Vector-valued self-normalized concentration inequalities beyond sub-Gaussianity ALT 2026
A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs JMLR 2025
Stochastic Online Instrumental Variable Regression: Regrets for Endogeneity and Bandit Feedback AAAI 2025
Optimal Exploration is no harder than Thompson Sampling AISTATS 2024
Directional Optimism for Safe Linear Bandits AISTATS 2024
Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification NIPS 2024
Adaptive Experimentation When You Can't Experiment NIPS 2024
Beyond task diversity: provable representation transfer for sequential multitask linear bandits NIPS 2024
On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice NIPS 2024
Symmetric Linear Bandits with Hidden Symmetry NIPS 2024
Improved Regret of Linear Ensemble Sampling NIPS 2024
Sparsity-Agnostic Linear Bandits with Adaptive Adversaries NIPS 2024
Improved Bayes Regret Bounds for Multi-Task Hierarchical Bayesian Bandit Algorithms NIPS 2024
A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity AISTATS 2024
Linear bandits with polylogarithmic minimax regret COLT 2024
Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit NIPS 2024
SPEED: Experimental Design for Policy Evaluation in Linear Heteroscedastic Bandits AISTATS 2024
Ensemble sampling for linear bandits: small ensembles suffice NIPS 2024
Multi-task Representation Learning for Pure Exploration in Linear Bandits ICML 2023
Does Sparsity Help in Learning Misspecified Linear Bandits? ICML 2023
On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits ICML 2023
A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs COLT 2023
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency COLT 2023
Anytime Model Selection in Linear Bandits NIPS 2023
Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits NIPS 2023