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

Showing 6170 of 1262 papers

TitleStatusHype
Decentralized Cooperative Stochastic BanditsCode0
Combinatorial Multi-armed Bandits for Resource AllocationCode0
Contextual Bandits with Large Action Spaces: Made PracticalCode0
Adaptive Linear Estimating EquationsCode0
Cascading Bandits for Large-Scale Recommendation ProblemsCode0
Causal Contextual Bandits with Adaptive ContextCode0
Scalable Exploration via Ensemble++Code0
Budgeted Multi-Armed Bandits with Asymmetric Confidence IntervalsCode0
Causally Abstracted Multi-armed BanditsCode0
Adaptive Experimentation with Delayed Binary FeedbackCode0
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Benchmark Results

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