conftrace_

multi-armed bandit

1098 papers

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Also known as

MAB

Co-occurring keywords

regret bound (1926) online learning (1777) stochastic optimization (1060) thompson sampling (237) upper confidence bound (197) regret minimization (315) online algorithm (445) sample complexity (1169) contextual bandit (381) best arm identification (85)

Papers

On the Asymptotic Optimality of Confidence Interval Based Algorithms for Fixed Confidence MABs AAAI 2025
Imprecise Multi-Armed Bandits: Representing Irreducible Uncertainty as a Zero-Sum Game JMLR 2025
Problem-dependent Regret for Lexicographic Multi-Armed Bandits with Adversarial Corruptions IJCAI 2025
Robust Performance Incentivizing Algorithms for Multi-Armed Bandits with Strategic Agents AAAI 2025
Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting AAAI 2025
Contextual Bandits with Stage-wise Constraints JMLR 2025
Randomised Optimism via Competitive Co-Evolution for Matrix Games with Bandit Feedback IJCAI 2025
Bandits with Concave Aggregated Reward IJCAI 2024
Improved Analysis for Bandit Learning in Matching Markets NIPS 2024
Pure Exploration in Bandits with Linear Constraints AISTATS 2024
Restless bandits with rewards generated by a linear Gaussian dynamical system L4DC 2024
Learning to Price Homogeneous Data NIPS 2024
Multi-armed bandits with guaranteed revenue per arm AISTATS 2024
The Best Arm Evades: Near-optimal Multi-pass Streaming Lower Bounds for Pure Exploration in Multi-armed Bandits COLT 2024
Improving Health Information Access in the World’s Largest Maternal Mobile Health Program via Bandit Algorithms AAAI 2024
Near-optimal Per-Action Regret Bounds for Sleeping Bandits AISTATS 2024
PRODuctive bandits: Importance Weighting No More NIPS 2024
Adaptive Anytime Multi-Agent Path Finding Using Bandit-Based Large Neighborhood Search AAAI 2024
Building Higher-Order Abstractions from the Components of Recommender Systems AAAI 2024
Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health AAAI 2024
Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability NIPS 2024
Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms NIPS 2024
Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds COLT 2024
Can Probabilistic Feedback Drive User Impacts in Online Platforms? AISTATS 2024
Exploration, Exploitation, and Engagement in Multi-Armed Bandits with Abandonment JMLR 2024