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 851–860 of 1262 papers

TitleStatusHype
Multinomial Logit Contextual Bandits: Provable Optimality and Practicality—0
Multi-Objective Generalized Linear Bandits—0
Multi-Player Approaches for Dueling Bandits—0
Multi-Player Bandits: A Trekking Approach—0
Multi-Player Bandits Revisited—0
Multi-Player Bandits Robust to Adversarial Collisions—0
Multiplayer Information Asymmetric Contextual Bandits—0
Multi-player Multi-armed Bandits with Collision-Dependent Reward Distributions—0
Multi-Player Multi-Armed Bandits with Finite Shareable Resources Arms: Learning Algorithms & Applications—0
Decentralized Heterogeneous Multi-Player Multi-Armed Bandits with Non-Zero Rewards on Collisions—0
Show:102550
← PrevPage 86 of 127Next →

Benchmark Results

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