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On Upper-Confidence Bound Policies for Switching Bandit Problems
8 references·16 citing·28 second hop
On Upper-Confidence Bound Policies for Switching Bandit Problems (2011)On Upper-Confidence Bound Policies for Sw…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 …Finite-time Analysis of the Multiarmed Bandit Problem (2002)Finite-time Analysis of the M…Tracking the Best Expert (1998)Tracking the Best ExpertA Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)A Decision-Theoretic Generali…Sample mean based index policies byO(logn) regret for the multi-armed bandit problem (1995)Sample mean based index polic…Restless bandits: activity allocation in a changing world (1988)Restless bandits: activity al…An empirical evaluation of active inference in multi-armed bandits (2021)An empirical evaluation of ac…Sliding-Window Thompson Sampling for Non-Stationary Settings (2020)Sliding-Window Thompson Sampl…Optimal Exploration–Exploitation in a Multi-armed Bandit Problem with Non-stationary Rewards (2019)Optimal Exploration–Exploitat…A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal, and Parameter-free (2019)A New Algorithm for Non-stati…Hedging the Drift: Learning to Optimize Under Non-Stationarity (2018)Hedging the Drift: Learning t…The non-stationary stochastic multi-armed bandit problem (2017)The non-stationary stochastic…Stochastic Online Shortest Path Routing: The Value of Feedback (2017)Stochastic Online Shortest Pa…Dynamic Privacy Pricing: A Multi-Armed Bandit Approach With Time-Variant Rewards (2016)Dynamic Privacy Pricing: A Mu…Chasing Demand: Learning and Earning in a Changing Environment (2016)Chasing Demand: Learning and …Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms (2014)Unimodal Bandits: Regret Lowe…Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards (2014)Stochastic Multi-Armed-Bandit…Sequential Learning for Multi-Channel Wireless Network Monitoring With Channel Switching Costs (2014)Sequential Learning for Multi…Sequential Transfer in Multi-armed Bandit with Finite Set of Models (2013)Sequential Transfer in Multi-…Informational confidence bounds for self-normalized averages and applications (2013)Informational confidence boun…Dynamic Pricing and Learning: Historical Origins, Current Research, and New Directions (2013)Dynamic Pricing and Learning:…Thompson Sampling: An Asymptotically Optimal Finite-Time Analysis (2012)Thompson Sampling: An Asympto…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)Exponentiated Gradient versus Gradient Descent for Linear Predictors (1997)How to use expert advice (1997)Using and combining predictors that specialize (1997)A Game of Prediction with Expert Advice (1998)Online portfolio selection (2014)Bandit Processes and Dynamic Allocation Indices (1979)On an index policy for restless bandits (1990)The Psychology and Neuroscience of Curiosity (2015)Bandit Algorithms (2020)Some aspects of the sequential design of experiments (1952)An Empirical Evaluation of Thompson Sampling (2011)Analysis of Thompson Sampling for the multi-armed bandit problem (2011)KULLBACK-LEIBLER UPPER CONFIDENCE BOUNDS FOR OPTIMAL SEQUENTIAL ALLOCATION (2013)Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments (2017)A Tutorial on Thompson Sampling (2018)Survey on speech emotion recognition: Features, classification schemes, and databases (2010)Linearly Parameterized Bandits (2010)Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms (2011)Combinatorial Network Optimization With Unknown Variables: Multi-Armed Bandits With Linear Rewards and Individual Observations (2012)Improved Algorithms for Linear Stochastic Bandits (2011)Introduction to Multi-Armed Bandits (2019)Time-Varying Gaussian Process Bandit Optimization (2016)A Change-Detection Based Framework for Piecewise-Stationary Multi-Armed Bandit Problem (2018)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)
this work references cited by second hop

References

  • 1997A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting20,469 cited
  • 2002Finite-time Analysis of the Multiarmed Bandit Problem5,980 cited
  • 2006Prediction, Learning, and Games3,176 cited
  • 2002The Nonstochastic Multiarmed Bandit Problem2,210 cited
  • 2003Using confidence bounds for exploitation-exploration trade-offs1,189 cited
  • 1988Restless bandits: activity allocation in a changing world1,174 cited
  • 1998Tracking the Best Expert557 cited
  • 1995Sample mean based index policies byO(logn) regret for the multi-armed bandit problem539 cited

Cited by

  • 2012Thompson Sampling: An Asymptotically Optimal Finite-Time Analysis381 cited
  • 2014Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards193 cited
  • 2016Chasing Demand: Learning and Earning in a Changing Environment139 cited
  • 2019Optimal Exploration–Exploitation in a Multi-armed Bandit Problem with Non-stationary Rewards101 cited
  • 2014Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms97 cited
  • 2014Sequential Learning for Multi-Channel Wireless Network Monitoring With Channel Switching Costs83 cited
  • 2018Hedging the Drift: Learning to Optimize Under Non-Stationarity

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83 cited
  • 2013Informational confidence bounds for self-normalized averages and applications74 cited
  • 2013Dynamic Pricing and Learning: Historical Origins, Current Research, and New Directions67 cited
  • 2019A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal, and Parameter-free62 cited
  • 2020Sliding-Window Thompson Sampling for Non-Stationary Settings61 cited
  • 2017Stochastic Online Shortest Path Routing: The Value of Feedback61 cited
  • 2016Dynamic Privacy Pricing: A Multi-Armed Bandit Approach With Time-Variant Rewards54 cited
  • 2013Sequential Transfer in Multi-armed Bandit with Finite Set of Models52 cited
  • 2017The non-stationary stochastic multi-armed bandit problem51 cited
  • 2021An empirical evaluation of active inference in multi-armed bandits45 cited