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Online Clustering of Bandits

arXiv 1401.8257 ↗First posted 31 Jan 2014cs.LG stat.MLcited by 99

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Abstract (arXiv)

We introduce a novel algorithmic approach to content recommendation based on adaptive clustering of exploration-exploitation ("bandit") strategies. We provide a sharp regret analysis of this algorithm in a standard stochastic noise setting, demonstrate its scalability properties, and prove its effectiveness on a number of artificial and real-world datasets. Our experiments show a significant increase in prediction performance over state-of-the-art methods for bandit problems.

Key facts. Cited by 99 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Jan 2014.

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Citing papers per year: 2021: 20; 2022: 19; 2023: 19; 2024: 14; 2025: 15; 2026: 12.

99 papers.

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  1. 2021RL for Latent MDPs: Regret Guarantees and a Lower Boundcited by 69
  2. 2021Meta-Thompson Samplingcited by 62
  3. 2021Federated Linear Contextual Banditscited by 61
  4. 2021Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-Profits in Improving Maternal and Child Healthcited by 43
  5. 2021Hierarchical Bayesian Banditscited by 33
  6. 2021Asynchronous Upper Confidence Bound Algorithms for Federated Linear Banditscited by 31
  7. 2021Local Clustering in Contextual Multi-Armed Banditscited by 29
  8. 2021No Regrets for Learning the Prior in Banditscited by 29
  9. 2022A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Banditscited by 28
  10. 2021Metadata-based Multi-Task Bandits with Bayesian Hierarchical Modelscited by 24
  11. 2021RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystemscited by 21
  12. 2021Multi-facet Contextual Bandits: A Neural Network Perspectivecited by 20
38 more
  1. 2023Graph Neural Banditscited by 20
  2. 2022Optimal Clustering with Bandit Feedbackcited by 15
  3. 2022Mixed-Effect Thompson Samplingcited by 14
  4. 2021Bandit Algorithms for Precision Medicinecited by 12
  5. 2023Online Clustering of Bandits with Misspecified User Modelscited by 12
  6. 2021Multitask Learning and Bandits via Robust Statisticscited by 11
  7. 2023Optimal Algorithms for Latent Bandits with Cluster Structurecited by 11
  8. 2022Meta-Learning for Simple Regret Minimizationcited by 10
  9. 2022Federated Online Clustering of Banditscited by 10
  10. 2023Concentrated Differential Privacy for Banditscited by 10
  11. 2023Neural Contextual Bandits for Personalized Recommendationcited by 10
  12. 2022Private and Byzantine-Proof Cooperative Decision-Makingcited by 9
  13. 2022Exploration in Linear Bandits with Rich Action Sets and its Implications for Inferencecited by 9
  14. 2022Non-stationary Bandits and Meta-Learning with a Small Set of Optimal Armscited by 8
  15. 2022Neural Bandit with Arm Group Graphcited by 8
  16. 2022Neural Collaborative Filtering Bandits via Meta Learningcited by 7
  17. 2023Optimal Multitask Linear Regression and Contextual Bandits under Sparse Heterogeneitycited by 7
  18. 2024GPT4Rec: Graph Prompt Tuning for Streaming Recommendationcited by 7
  19. 2024Meta Clustering of Neural Banditscited by 7
  20. 2024Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Userscited by 6
  21. 2021Maximizing and Satisficing in Multi-armed Bandits with Graph Informationcited by 5
  22. 2022Breaking the √T Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Banditscited by 5
  23. 2022Dynamic Global Sensitivity for Differentially Private Contextual Banditscited by 5
  24. 2022Reward-Mixing MDPs with a Few Latent Contexts are Learnablecited by 5
  25. 2024Diffusion Models Meet Contextual Banditscited by 5
  26. 2021Adaptive Clustering and Personalization in Multi-Agent Stochastic Linear Banditscited by 4
  27. 2022Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanismscited by 4
  28. 2022Semi-Parametric Contextual Bandits with Graph-Laplacian Regularizationcited by 4
  29. 2024AxiomVision: Accuracy-Guaranteed Adaptive Visual Model Selection for Perspective-Aware Video Analyticscited by 4
  30. 2025Generalized Low-Rank Matrix Contextual Bandits with Graph Informationcited by 4
  31. 2022Thompson Sampling for Robust Transfer in Multi-Task Banditscited by 3
  32. 2022Tractable Optimality in Episodic Latent MABscited by 3
  33. 2023Context-lumpable stochastic banditscited by 3
  34. 2023Online Corrupted User Detection and Regret Minimizationcited by 3
  35. 2024Expert with Clustering: Hierarchical Online Preference Learning Frameworkcited by 3
  36. 2024Federated Linear Contextual Bandits with Heterogeneous Clientscited by 3
  37. 2025Demystifying Online Clustering of Bandits: Enhanced Exploration Under Stochastic and Smoothed Adversarial Contextscited by 3
  38. 2025Graph Feedback Bandits on Similar Arms: With and Without Graph Structurescited by 3

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