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On Top-k selection in multi-armed bandits and hidden bipartite graphs
10 references·1 citing·25 second hopsampled
On Top-k selection in multi-armed bandits and hidden bipartite graphs (2015)On Top-k selection in multi-armed bandits…Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing (2014)Optimal PAC Multiple Arm Iden…Combinatorial Pure Exploration of Multi-Armed Bandits (2014)Combinatorial Pure Exploratio…Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Regret Analysis of Stochastic…PAC Subset Selection in Stochastic Multi-armed Bandits (2012)PAC Subset Selection in Stoch…Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence (2012)Best Arm Identification: A Un…Pure exploration in finitely-armed and continuous-armed bandits (2010)Pure exploration in finitely-…Efficient Selection of Multiple Bandit Arms: Theory and Practice (2010)Efficient Selection of Multip…Best Arm Identification in Multi-Armed Bandits (2010)Best Arm Identification in Mu…Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems (2006)Action Elimination and Stoppi…The Sample Complexity of Exploration in the Multi-Armed Bandit Problem (2004)The Sample Complexity of Expl…Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration (2017)Nearly Optimal Sampling Algor…Some aspects of the sequential design of experiments (1952)Finite-time Analysis of the Multiarmed Bandit Problem (2002)Prediction, Learning, and Games (2006)Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)Bandit Algorithms (2020)The Nonstochastic Multiarmed Bandit Problem (2002)Qualitative Multi-Armed Bandits: A Quantile-Based Approach (2015)On Sequential Elimination Algorithms for Best-Arm Identification in Multi-Armed Bandits (2017)Collaborative Learning with Limited Interaction: Tight Bounds for Distributed Exploration in Multi-armed Bandits (2019)A Stochastic Approximation Method (1951)Introduction to Online Convex Optimization (2016)Introduction to Online Convex Optimization (2016)A fully sequential procedure for indifference-zone selection in simulation (2001)Learning with Limited Rounds of Adaptivity: Coin Tossing, Multi-Armed Bandits, and Ranking from Pairwise Comparisons. (2017)Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications (2018)Gambling in a rigged casino: The adversarial multi-armed bandit problem (2002)Introduction to Multi-Armed Bandits (2019)Combinatorial Multi-Armed Bandit with General Reward Functions (2016)Non-Asymptotic Pure Exploration by Solving Games (2019)Pure Exploration with Multiple Correct Answers (2019)On the Complexity of Best Arm Identification in Multi-Armed Bandit Models (2014)A unified framework for stochastic optimization (2018)Information Complexity in Bandit Subset Selection (2013)Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization (2016)Best-arm identification algorithms for multi-armed bandits in the fixed confidence setting (2014)
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References

  • 2012Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems1,483 cited
  • 2010Best Arm Identification in Multi-Armed Bandits448 cited
  • 2006Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems444 cited
  • 2004The Sample Complexity of Exploration in the Multi-Armed Bandit Problem318 cited
  • 2010Pure exploration in finitely-armed and continuous-armed bandits188 cited
  • 2012PAC Subset Selection in Stochastic Multi-armed Bandits188 cited
  • 2012Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence132 cited
  • 2014Combinatorial Pure Exploration of Multi-Armed Bandits104 cited
  • 2010Efficient Selection of Multiple Bandit Arms: Theory and Practice64 cited
  • 2014Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing39 cited

Cited by

  • 2017Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration26 cited

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