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SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits
12 references·5 citing·29 second hop
SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits (2018)SIC-MMAB: Synchronisation Involves Commun…Batched bandit problems (2016)Batched bandit problemsOptimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays (2015)Optimal Regret Analysis of Th…Multi-Player Bandits -- a Musical Chairs Approach (2015)Multi-Player Bandits -- a Mus…Decentralized Learning for Multiplayer Multiarmed Bandits (2014)Decentralized Learning for Mu…Concurrent Bandits and Cognitive Radio Networks (2014)Concurrent Bandits and Cognit…Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Regret Analysis of Stochastic…The multi-armed bandit problem with covariates (2011)The multi-armed bandit proble…Distributed Learning in Multi-Armed Bandit With Multiple Players (2010)Distributed Learning in Multi…Finite-time Analysis of the Multiarmed Bandit Problem (2002)Finite-time Analysis of the M…Sample mean based index policies byO(logn) regret for the multi-armed bandit problem (1995)Sample mean based index polic…Asymptotically efficient allocation rules for the multiarmed bandit problem with multiple plays-Part I: I.I.D. rewards (1987)Asymptotically efficient allo…Some aspects of the sequential design of experiments (1952)Some aspects of the sequentia…Multiplayer Bandits: A Trekking Approach (2021)Multiplayer Bandits: A Trekki…Multiplayer Bandits Without Observing Collision Information (2021)Multiplayer Bandits Without O…Federated Multi-armed Bandits with Personalization (2021)Federated Multi-armed Bandits…Decentralized Learning in Online Queuing Systems (2021)Decentralized Learning in Onl…Optimal Algorithms for Multiplayer Multi-Armed Bandits (2019)Optimal Algorithms for Multip…Bandit Problems, Sequential Allocation of Experiments. (1987)Batched Multi-armed Bandits Problem (2019)Counterfactual Reward Modification for Streaming Recommendation with Delayed Feedback (2021)Experimenting in Equilibrium (2021)A Method of Sampling Inspection (1929)Experimental Determination of the Maximum of a Function (1941)A Stochastic Approximation Method (1951)The Nonstochastic Multiarmed Bandit Problem (2002)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Prediction, Learning, and Games (2006)Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)Introduction to Online Convex Optimization (2016)Introduction to Online Convex Optimization (2016)The Complexity of Optimal Queuing Network Control (1999)Channel Selection for Network-Assisted D2D Communication via No-Regret Bandit Learning With Calibrated Forecasting (2014)Distributed Clustering of Linear Bandits in Peer to Peer Networks (2016)Risk-Averse Multi-Armed Bandit Problems Under Mean-Variance Measure (2016)Multi-Armed Bandit Allocation Indices (1989)Multi-Armed Bandit Allocation Indices. (1990)Using confidence bounds for exploitation-exploration trade-offs (2003)The Continuum-Armed Bandit Problem (1995)Indexability of Restless Bandit Problems and Optimality of Whittle Index for Dynamic Multichannel Access (2010)Bandit Algorithms (2020)1 1 Online Learning of Rested and Restless Bandits (2012)Learning in a Changing World: Restless Multiarmed Bandit With Unknown Dynamics (2012)Delay and Cooperation in Nonstochastic Bandits (2016)Federated Recommendation System via Differential Privacy (2020)Federated Multi-Armed Bandits (2021)The best of both worlds: stochastic and adversarial bandits (2012)
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References

  • 2002Finite-time Analysis of the Multiarmed Bandit Problem6,033 cited
  • 1952Some aspects of the sequential design of experiments2,183 cited
  • 2012Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems1,483 cited
  • 1995Sample mean based index policies byO(logn) regret for the multi-armed bandit problem539 cited
  • 2010Distributed Learning in Multi-Armed Bandit With Multiple Players386 cited
  • 1987Asymptotically efficient allocation rules for the multiarmed bandit problem with multiple plays-Part I: I.I.D. rewards358 cited
  • 2014Decentralized Learning for Multiplayer Multiarmed Bandits158 cited
  • 2011The multi-armed bandit problem with covariates153 cited
  • 2016Batched bandit problems137 cited
  • 2015Multi-Player Bandits -- a Musical Chairs Approach117 cited
  • 2015Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays104 cited
  • 2014Concurrent Bandits and Cognitive Radio Networks79 cited

Cited by

  • 2019Optimal Algorithms for Multiplayer Multi-Armed Bandits42 cited
  • 2021Federated Multi-armed Bandits with Personalization35 cited
  • 2021Multiplayer Bandits Without Observing Collision Information

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30 cited
  • 2021Multiplayer Bandits: A Trekking Approach26 cited
  • 2021Decentralized Learning in Online Queuing Systems10 cited