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Multi-Armed Bandits

1044 directly classified papers

Papers per year

Papers

Sparsity-Agnostic Linear Bandits with Adaptive Adversaries NIPS 2024
PRODuctive bandits: Importance Weighting No More NIPS 2024
Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms NIPS 2024
Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox NIPS 2024
Online Learning with Sublinear Best-Action Queries NIPS 2024
Improved Regret of Linear Ensemble Sampling NIPS 2024
A Unified Framework for Discovering Discrete Symmetries AISTATS 2024
Best-of-Both-Worlds Algorithms for Linear Contextual Bandits AISTATS 2024
Online learning in bandits with predicted context AISTATS 2024
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits NIPS 2024
Global Rewards in Restless Multi-Armed Bandits NIPS 2024
Sequential learning of the Pareto front for multi-objective bandits AISTATS 2024
Materials Discovery using Max K-Armed Bandit JMLR 2024
Eliciting Kemeny Rankings AAAI 2024
Delayed Feedback in Generalised Linear Bandits Revisited AISTATS 2023
Distributionally Robust Policy Gradient for Offline Contextual Bandits AISTATS 2023
Revisiting Simple Regret: Fast Rates for Returning a Good Arm ICML 2023
On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits ICML 2023
Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits ICML 2023
Pareto Regret Analyses in Multi-objective Multi-armed Bandit ICML 2023
Vector Optimization with Stochastic Bandit Feedback AISTATS 2023
Competing for Shareable Arms in Multi-Player Multi-Armed Bandits ICML 2023
Boosted Off-Policy Learning AISTATS 2023
Tight Regret Bounds for Single-pass Streaming Multi-armed Bandits ICML 2023
Nested Elimination: A Simple Algorithm for Best-Item Identification From Choice-Based Feedback ICML 2023