Thompson Sampling

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7 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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  1. Expected Sample Complexity in Multi-Armed Bandits

    Oct 7, 2026Nadav Sukenik, Nadav MerlisMulti-Armed BanditsRegret Minimization

    Technion – Institute of Technology

  2. Structure, Not Belief: Correlated Thompson Sampling from LLM-Derived Covariance in Combinatorial Semi-Bandits

    Oct 5, 2026Vikram Kakaria, Anish Kataria, Anany KotawalaThompson SamplingMulti-Armed Bandits

    Princeton University

  3. Ranking Bandits for Carousel Interfaces with Observable Browsing Depth

    Oct 4, 2026Takuma Yasuda, Atsuyoshi NakamuraThompson SamplingMulti-Armed Bandits

    Graduate School of Information Science and Technology Hokkaido University Sapporo, Japan

  4. When May a Bandit Leave Its Anchor? E-Process-Authorized Thompson Sampling under Non-stationarity

    Oct 2, 2026Mayand Gulati, Kerong Wang, WeiChen AuThompson SamplingNon-Stationary Bandits

    UC Santa Barbara · Purdue University

  5. Risk-Aware Adaptive Evaluation: Finding High-Impact Failures Under Limited Budgets

    Sep 30, 2026Priyanath Maji, Spandan Ghose ChowdhuryThompson SamplingAI Agent Evaluation

    Georgia Institute of Technology Atlanta, GA 30332

  6. A Unified Optimism-Agnostic Framework for Linear Bandits over Spherical Action Sets

    Sep 26, 2026Arda Güçlü, Subhonmesh Bose, John R. BirgeMulti-Armed BanditsUCB Algorithms

    University of Chicago Booth School of Business, Chicago, IL 60637

  7. Exact Bayes Regret and Asymptotic Optimality in High-Dimensional Gaussian Bandits

    Sep 23, 2026Prakhar Singhvi, Yi Zou, Abhishek BhattacharjeeThompson SamplingMulti-Armed Bandits

    Abstract Math Institute

  8. Odds-Ratio Thompson Sampling: A Specification and Design Guide for Contrast-Based Multi-Armed Bandits

    Sep 17, 2026Sulgi KimThompson SamplingMulti-Armed Bandits

    Independent researcher

  9. Thompson Sampling for Non-Monotone Convex Ridge Bandits: Monotonicity Is Not Needed for Polynomial Regret

    Sep 10, 2026Xuan LiThompson SamplingBandit Convex Optimization

    University of New South Wales, Sydney, Australia

  10. Posterior Tempering Explains Variance Inflation in Linear and Generalized Linear Thompson Sampling

    Sep 2, 2026Prateek Jaiswal, Debdeep Pati, Anirban Bhattacharya +1Thompson SamplingMulti-Armed Bandits

    Daniels School of Business, Purdue University. · Department of Statistics, University of Wisconsin-Madison. · Department of Statistics, Texas A&M University.

  11. Improved Regret Analysis for Parallel Gaussian Process Bandit Optimization

    Aug 17, 2026Shion Takeno, Shogo IwazakiThompson SamplingMulti-Armed Bandits

    Nagoya University · MI-6 Ltd.

  12. LLM-Derived Priors for Thompson Sampling in Cold-Start Comment Recommendation

    Aug 4, 2026Eugene Lee, Oseong Choi, Byungsoo Kang +1Thompson SamplingCold-Start Recommendation

    NAVER WEBTOON South Korea

  13. On-Policy and Off-Policy Learning for Large Action Spaces

    Jul 30, 2026Imad AoualiThompson SamplingMulti-Armed Bandits

    Institut Polytechnique de Paris · Ecole nationale de la statistique et de l’administration économique · Ecole doctorale n◦574 Ecole Doctorale de Mathématique Hadamard (EDMH)

  14. Periodic Bootstrap Thompson Sampling For Periodically Non-Stationary Bandit Problems

    Jul 18, 2026Boning ShaoThompson SamplingNon-Stationary Bandits

    Faculty of Science, University of Hong Kong, Hong Kong, China

  15. Information-Directed Sampling for Causal Bandits

    Jul 17, 2026Muhammad Qasim Elahi, Murat Kocaoglu, Mahsa GhasemiThompson SamplingMulti-Armed Bandits

    School of Electrical and Computer Engineering, Purdue University · School of Computer Science, Johns Hopkins University

  16. Thompson Sampling Is 2-Competitive for Mistakes

    Jul 14, 2026Mark Sellke, Gregory ValiantThompson SamplingMulti-Armed Bandits

  17. Link Adaptation Using Joint-Thompson Sampling

    Jul 13, 2026Vignatha Vinjam, Manjunath Kolavennu, Myna Vajha +1Thompson SamplingMulti-Armed Bandits

    Department of EE, IIT Hyderabad · Department of AI, IIT Hyderabad

  18. Randomized Exploration for Linear Bandits via Absolute Perturbations

    Jun 26, 2026Toshinori Kitamura, Shuai Liu, Csaba SzepesváriThompson SamplingMulti-Armed Bandits

    Department of Computing Science, University of Alberta, Canada

  19. Flow-Corrected Thompson Sampling for Non-Stationary Contextual Bandits

    Jun 22, 2026AmirHossein Naghdi, Ali BaheriThompson SamplingNon-Stationary Bandits

    Sharif University of Technology, Iran · Rochester Institute of Technology, USA

  20. AdaPrivate-TS: Private Thompson Sampling for Contextual Bandits with Privacy Amplification

    Jun 19, 2026Mohammadreza Riyazat, Eranga UkwattaThompson SamplingDifferential Privacy

    School of Engineering, University of Guelph, Guelph, ON, Canada.

  21. Bayesian Anytime Pareto Set Identification for Multi-Objective Multi-Armed Bandits

    Jun 17, 2026Lennert Saerens, Bram Silue, Eleni Litsa +2Thompson SamplingMulti-Armed Bandits

    Artificial Intelligence Lab, Departement of Computer Science, Vrije Universiteit Brussel, Brussels, Belgium · imec, Leuven, Belgium

  22. Asymptotic Optimality of Thompson Sampling for Risk-Averse Bandits with Sub-Gaussian Rewards

    Jun 8, 2026Joel Q. L. ChangThompson SamplingMulti-Armed Bandits

  23. MINTS: Minimalist Thompson Sampling

    Jun 1, 2026Kaizheng WangThompson SamplingMulti-Armed Bandits

    Department of IEOR and Data Science Institute, Columbia University.

  24. Variance-sensitive Thompson sampling for generalised linear bandits, revisited

    May 29, 2026Tom Perneczky, Marc Abeille, David JanzThompson SamplingMulti-Armed Bandits

    University of Oxford · Criteo AI Lab

  25. Contextual Scalarisation Thompson Sampling for multi-objective decisions in public media

    May 29, 2026Théo Maëtz, Luc Guillet, Andrea CavallaroThompson SamplingRecommender Systems

    Radio Télévision Suisse, Geneva, Switzerland · EPFL, Lausanne, Switzerland

  26. Adaptive Policy Learning Under Unknown Network Interference

    May 11, 2026Aidan Gleich, Eric Laber, Alexander VolfovskyThompson SamplingMulti-Armed Bandits

    Department of Statistical Science Duke University

  27. Sample-Mean Anchored Thompson Sampling for Offline-to-Online Learning with Distribution Shift

    May 11, 2026Bochao Li, Yao Fu, Wei Chen +1Distribution Shift RobustnessThompson Sampling

    Southern University of Science and Technology · Microsoft Research

  28. PFN-TS: Thompson Sampling for Contextual Bandits via Prior-Data Fitted Networks

    May 11, 2026Yan Shuo Tan, Kenyon Ng, Ruizhe Deng +3Thompson SamplingPrior-Data Fitted Networks

    National University of Singapore · Monash University · Renmin University of China +1

  29. Worst-Case Regret Bounds for Combinatorial Thompson Sampling in Sleeping Semi-Bandits

    May 10, 2026Zhiming Huang, Bingshan Hu, Jianping PanThompson SamplingMulti-Armed Bandits

    Paul G. Allen School of Computer Science & Engineering, University of Washington, WA, USA · Department of Computer Science, University of British Columbia, BC, Canada · Department of Computer Science, University of Victoria, BC, Canada

  30. POETS: Uncertainty-Aware LLM Optimization via Compute-Efficient Policy Ensembles

    May 8, 2026Nicolas Menet, Andreas Krause, Abbas RahimiThompson SamplingBlack-Box Optimization

    IBM Research – Zurich · Department of Computer Science, ETH Zürich