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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 26–50 of 1262 papers

Title	Date	Tasks	Status	Hype	Score
Carousel Personalization in Music Streaming Apps with Contextual Bandits	Sep 14, 2020	Multi-Armed Bandits	CodeCode Available	1	5
Deep Bandits Show-Off: Simple and Efficient Exploration with Deep Networks	May 10, 2021	Efficient ExplorationMulti-Armed Bandits	CodeCode Available	1	5
Neural Thompson Sampling	Oct 2, 2020	Multi-Armed BanditsThompson Sampling	CodeCode Available	1	5
LASeR: Learning to Adaptively Select Reward Models with Multi-Armed Bandits	Oct 2, 2024	Instruction FollowingMath	CodeCode Available	1	5
Langevin Monte Carlo for Contextual Bandits	Jun 22, 2022	Multi-Armed BanditsThompson Sampling	CodeCode Available	1	5
Discovering Minimal Reinforcement Learning Environments	Jun 18, 2024	continuous-controlContinuous Control	CodeCode Available	1	5
Efficient Contextual Bandits with Continuous Actions	Jun 10, 2020	Multi-Armed Bandits	CodeCode Available	1	5
Multiplayer Multi-armed Bandits for Optimal Assignment in Heterogeneous Networks	Jan 12, 2019	Multi-Armed Bandits	CodeCode Available	1	5
Implicitly normalized forecaster with clipping for linear and non-linear heavy-tailed multi-armed bandits	May 11, 2023	Multi-Armed Bandits	CodeCode Available	1	5
Pervasive Machine Learning for Smart Radio Environments Enabled by Reconfigurable Intelligent Surfaces	May 8, 2022	BIG-bench Machine LearningDeep Reinforcement Learning	CodeCode Available	1	5
A Modern Introduction to Online Learning	Dec 31, 2019	AllMulti-Armed Bandits	CodeCode Available	1	5
Federated Multi-Armed Bandits	Jan 28, 2021	Federated LearningMulti-Armed Bandits	CodeCode Available	1	5
Combinatorial Multi-armed Bandits for Resource Allocation	May 10, 2021	Multi-Armed Bandits	CodeCode Available	0	5
Adapting multi-armed bandits policies to contextual bandits scenarios	Nov 11, 2018	Binary ClassificationClassification	CodeCode Available	0	5
Combining Diverse Information for Coordinated Action: Stochastic Bandit Algorithms for Heterogeneous Agents	Aug 6, 2024	Multi-Armed BanditsSensitivity	CodeCode Available	0	5
Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback	Sep 4, 2019	Multi-Armed Bandits	CodeCode Available	0	5
Causally Abstracted Multi-armed Bandits	Apr 26, 2024	Decision MakingMulti-Armed Bandits	CodeCode Available	0	5
Combinatorial Bandits under Strategic Manipulations	Feb 25, 2021	Multi-Armed BanditsRecommendation Systems	CodeCode Available	0	5
Flooding with Absorption: An Efficient Protocol for Heterogeneous Bandits over Complex Networks	Mar 9, 2023	Decision MakingMulti-Armed Bandits	CodeCode Available	0	5
Budgeted Multi-Armed Bandits with Asymmetric Confidence Intervals	Jun 12, 2023	Multi-Armed Bandits	CodeCode Available	0	5
Cascading Bandits for Large-Scale Recommendation Problems	Mar 17, 2016	Multi-Armed BanditsRecommendation Systems	CodeCode Available	0	5
Safe and Adaptive Decision-Making for Optimization of Safety-Critical Systems: The ARTEO Algorithm	Nov 10, 2022	Decision MakingDecision Making Under Uncertainty	CodeCode Available	0	5
Best Arm Identification with Fixed Budget: A Large Deviation Perspective	Dec 19, 2023	Multi-Armed Bandits	CodeCode Available	0	5
Bandit-Based Monte Carlo Optimization for Nearest Neighbors	May 21, 2018	ClusteringMulti-Armed Bandits	CodeCode Available	0	5
Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards	Jun 3, 2019	Multi-Armed Bandits	CodeCode Available	0	5

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	NeuralLinear FullPosterior-MR	Cumulative regret	1.92	—	Unverified
2	Linear FullPosterior-MR	Cumulative regret	1.82	—	Unverified