SOTAVerified

Multi-Armed Bandits

Multi-armed bandits refer to a task where a fixed amount of resources must be allocated between competing resources that maximizes expected gain. Typically these problems involve an exploration/exploitation trade-off.

( Image credit: Microsoft Research )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 651–675 of 1262 papers

TitleStatusHype
Achieving the Pareto Frontier of Regret Minimization and Best Arm Identification in Multi-Armed Bandits—0
Almost Optimal Batch-Regret Tradeoff for Batch Linear Contextual Bandits—0
Bandits Don't Follow Rules: Balancing Multi-Facet Machine Translation with Multi-Armed Bandits—0
Query-Reward Tradeoffs in Multi-Armed Bandits—0
Deep Upper Confidence Bound Algorithm for Contextual Bandit Ranking of Information Selection—0
A Model Selection Approach for Corruption Robust Reinforcement Learning—0
EE-Net: Exploitation-Exploration Neural Networks in Contextual BanditsCode1
Feel-Good Thompson Sampling for Contextual Bandits and Reinforcement Learning—0
Asymptotic Performance of Thompson Sampling in the Batched Multi-Armed Bandits—0
Batched Thompson Sampling—0
Adapting Bandit Algorithms for Settings with Sequentially Available Arms—0
Causal Contextual Bandits with Targeted Interventions—0
Regularized-OFU: an efficient algorithm for general contextual bandit with optimization oracles—0
Expected Improvement-based Contextual Bandits—0
Batched Bandits with Crowd Externalities—0
Risk averse non-stationary multi-armed bandits—0
Robust Generalization of Quadratic Neural Networks via Function Identification—0
Generalized Translation and Scale Invariant Online Algorithm for Adversarial Multi-Armed Bandits—0
Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-Profits in Improving Maternal and Child Health—0
Estimation of Warfarin Dosage with Reinforcement LearningCode0
Exploiting Heterogeneity in Robust Federated Best-Arm Identification—0
Improved Algorithms for Misspecified Linear Markov Decision Processes—0
Best-Arm Identification in Correlated Multi-Armed Bandits—0
Online Learning for Cooperative Multi-Player Multi-Armed Bandits—0
Max-Utility Based Arm Selection Strategy For Sequential Query Recommendations—0
Show:102550
← PrevPage 27 of 51Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1NeuralLinear FullPosterior-MRCumulative regret1.92—Unverified
2Linear FullPosterior-MRCumulative regret1.82—Unverified