conftrace_

multi-armed bandit

1098 papers

Explore in graph

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

Thompson Sampling for Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit AAAI 2024
Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs AAAI 2024
Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds COLT 2024
Bandit Pareto Set Identification: the Fixed Budget Setting AISTATS 2024
Bandits with Ranking Feedback NIPS 2024
Optimal Top-Two Method for Best Arm Identification and Fluid Analysis NIPS 2024
Can Probabilistic Feedback Drive User Impacts in Online Platforms? AISTATS 2024
Finite-time Analysis of Globally Nonstationary Multi-Armed Bandits JMLR 2024
Restless bandits with rewards generated by a linear Gaussian dynamical system L4DC 2024
Optimal Learning Policies for Differential Privacy in Multi-armed Bandits JMLR 2024
Improving Health Information Access in the World’s Largest Maternal Mobile Health Program via Bandit Algorithms AAAI 2024
Piecewise-Stationary Bandits with Knapsacks NIPS 2024
Queueing Matching Bandits with Preference Feedback NIPS 2024
ADR-X: ANN-Assisted Wireless Link Rate Adaptation for Compute-Constrained Embedded Gaming Devices NSDI 2024
Forced Exploration in Bandit Problems AAAI 2024
Federated X-armed Bandit AAAI 2024
Information Capacity Regret Bounds for Bandits with Mediator Feedback JMLR 2024
The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models AAAI 2024
Improved Bandits in Many-to-One Matching Markets with Incentive Compatibility AAAI 2024
Learning Fair Division from Bandit Feedback AISTATS 2024
Near-optimal Per-Action Regret Bounds for Sleeping Bandits AISTATS 2024
No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting NIPS 2024
Directional Optimism for Safe Linear Bandits AISTATS 2024
Learning Human-like Representations to Enable Learning Human Values NIPS 2024
Stealthy Adversarial Attacks on Stochastic Multi-Armed Bandits AAAI 2024