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Regret Bounds and Minimax Policies under Partial Monitoring
8 references·16 citing·28 second hop
Regret Bounds and Minimax Policies under Partial Monitoring (2010)Regret Bounds and Minimax Policies under …Exploration–exploitation tradeoff using variance estimates in multi-armed bandits (2009)Exploration–exploitation trad…Prediction, Learning, and Games (2006)Prediction, Learning, and Gam…Using confidence bounds for exploitation-exploration trade-offs (2003)Using confidence bounds for e…The Nonstochastic Multiarmed Bandit Problem (2002)The Nonstochastic Multiarmed …Gambling in a rigged casino: The adversarial multi-armed bandit problem (2002)Gambling in a rigged casino: …Finite-time Analysis of the Multiarmed Bandit Problem (2002)Finite-time Analysis of the M…How to use expert advice (1997)How to use expert adviceSome aspects of the sequential design of experiments (1952)Some aspects of the sequentia…Bandits and Experts in Metric Spaces (2019)Bandits and Experts in Metric…On Bayesian index policies for sequential resource allocation (2018)On Bayesian index policies fo…Batched bandit problems (2016)Batched bandit problemsAdaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems (2016)Adaptive Contract Design for …The multi-armed bandit problem with covariates (2013)The multi-armed bandit proble…Risk-Aversion in Multi-armed Bandits (2013)Risk-Aversion in Multi-armed …Regret in Online Combinatorial Optimization (2013)Regret in Online Combinatoria…Online Learning for Linearly Parametrized Control Problems (2013)Online Learning for Linearly …Kullback–Leibler upper confidence bounds for optimal sequential allocation (2013)Kullback–Leibler upper confid…The best of both worlds: stochastic and adversarial bandits (2012)The best of both worlds: stoc…Optimistic bayesian sampling in contextual-bandit problems (2012)Optimistic bayesian sampling …On Bayesian Upper Confidence Bounds for Bandit Problems (2012)On Bayesian Upper Confidence …Dynamic pricing with limited supply (2012)Dynamic pricing with limited …The multi-armed bandit problem with covariates (2011)The multi-armed bandit proble…Introduction to Online Optimization (2011)Introduction to Online Optimi…A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences (2011)A Finite-Time Analysis of Mul…A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Online Learning and Online Convex Optimization (2011)Online Learning and Online Convex Optimization (2012)Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Theory of games and economic behavior (2019)Bandit Processes and Dynamic Allocation Indices (1979)From Ads to Interventions: Contextual Bandits in Mobile Health (2017)Linear Thompson sampling revisited (2017)MNL-Bandit: A Dynamic Learning Approach to Assortment Selection (2019)Contributions to the theory of games. (1960)The Asymptotic Theory of Extreme Order Statistics (1990)Tracking the Best Expert (1998)Adaptive Game Playing Using Multiplicative Weights (1999)Efficient algorithms for online decision problems (2004)A Stochastic Approximation Method (1951)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Multi-Armed Bandit Allocation Indices. (1990)The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond (2011)Thompson Sampling: An Asymptotically Optimal Finite-Time Analysis (2012)Intrinsic motivation, curiosity, and learning (2016)Improved Algorithms for Linear Stochastic Bandits (2011)Introduction to Multi-Armed Bandits (2019)Bandit Algorithms (2020)Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits (2014)Combinatorial Bandits Revisited (2015)Learning to Optimize via Information-Directed Sampling (2017)Online convex optimization in the bandit setting: gradient descent without a gradient (2004)Multi-armed Bandit Algorithms and Empirical Evaluation (2005)
this work references cited by second hop

References

  • 2002Finite-time Analysis of the Multiarmed Bandit Problem5,980 cited
  • 2006Prediction, Learning, and Games3,176 cited
  • 2002The Nonstochastic Multiarmed Bandit Problem2,210 cited
  • 1952Some aspects of the sequential design of experiments2,183 cited
  • 2003Using confidence bounds for exploitation-exploration trade-offs1,189 cited
  • 2002Gambling in a rigged casino: The adversarial multi-armed bandit problem741 cited
  • 1997How to use expert advice631 cited
  • 2009Exploration–exploitation tradeoff using variance estimates in multi-armed bandits571 cited

Cited by

  • 2012Optimistic bayesian sampling in contextual-bandit problems213 cited
  • 2013Regret in Online Combinatorial Optimization210 cited
  • 2012On Bayesian Upper Confidence Bounds for Bandit Problems210 cited
  • 2013Kullback–Leibler upper confidence bounds for optimal sequential allocation181 cited
  • 2011The multi-armed bandit problem with covariates153 cited
  • 2012The best of both worlds: stochastic and adversarial bandits144 cited
  • 2016Batched bandit problems137 cited
  • 2013

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The multi-armed bandit problem with covariates
122 cited
  • 2011A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences121 cited
  • 2011Introduction to Online Optimization108 cited
  • 2012Dynamic pricing with limited supply98 cited
  • 2018On Bayesian index policies for sequential resource allocation97 cited
  • 2013Risk-Aversion in Multi-armed Bandits97 cited
  • 2013Online Learning for Linearly Parametrized Control Problems90 cited
  • 2019Bandits and Experts in Metric Spaces75 cited
  • 2016Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems75 cited