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

Best-of-Three-Worlds Linear Bandit Algorithm with Variance-Adaptive Regret Bounds COLT 2023
Linear Partial Monitoring for Sequential Decision Making: Algorithms, Regret Bounds and Applications JMLR 2023
Multi-task Representation Learning for Pure Exploration in Linear Bandits ICML 2023
Exploration in Linear Bandits with Rich Action Sets and its Implications for Inference AISTATS 2023
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds NIPS 2023
Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms COLT 2023
No-Regret Linear Bandits beyond Realizability UAI 2023
Thresholded linear bandits AISTATS 2023
Does Sparsity Help in Learning Misspecified Linear Bandits? ICML 2023
Stochastic Contextual Bandits with Long Horizon Rewards AAAI 2023
Risk-aware linear bandits with convex loss AISTATS 2023
An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits NIPS 2023
Dynamical Linear Bandits ICML 2023
On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits ICML 2023
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency COLT 2023
Best-of-three-worlds Analysis for Linear Bandits with Follow-the-regularized-leader Algorithm COLT 2023
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits NIPS 2022
Linear Bandit Algorithms with Sublinear Time Complexity ICML 2022
Near Instance Optimal Model Selection for Pure Exploration Linear Bandits AISTATS 2022
Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs NIPS 2022
Online Learning and Pricing with Reusable Resources: Linear Bandits with Sub-Exponential Rewards ICML 2022
Breaking the $\sqrtT$ Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits ICML 2022
Metalearning Linear Bandits by Prior Update AISTATS 2022
Corralling a Larger Band of Bandits: A Case Study on Switching Regret for Linear Bandits COLT 2022
When Are Linear Stochastic Bandits Attackable? ICML 2022