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Adaptive Ensemble Learning With Confidence Bounds
13 references·0 citing·26 second hop
Adaptive Ensemble Learning With Confidence Bounds (2016)Adaptive Ensemble Learning With Confidenc…Distributed Online Learning via Cooperative Contextual Bandits (2015)Distributed Online Learning v…Learning to Optimize via Posterior Sampling (2014)Learning to Optimize via Post…Follow the Leader If You Can, Hedge If You Must (2013)Follow the Leader If You Can,…Improved Algorithms for Linear Stochastic Bandits (2011)Improved Algorithms for Linea…Contextual Multi-Armed Bandits (2010)Contextual Multi-Armed BanditsA parameter-free hedging algorithm (2009)A parameter-free hedging algo…Prediction, Learning, and Games (2006)Prediction, Learning, and Gam…The Nonstochastic Multiarmed Bandit Problem (2002)The Nonstochastic Multiarmed …Finite-time Analysis of the Multiarmed Bandit Problem (2002)Finite-time Analysis of the M…Adaptive and self-confident on-line learning algorithms (2002)Adaptive and self-confident o…Tracking the Best Expert (1998)Tracking the Best ExpertHow to use expert advice (1997)How to use expert adviceA Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)A Decision-Theoretic Generali…Online Learning and Online Convex Optimization (2011)Online Learning and Online Convex Optimization (2012)Theory of games and economic behavior (2019)Exponentiated Gradient versus Gradient Descent for Linear Predictors (1997)A Game of Prediction with Expert Advice (1998)On Upper-Confidence Bound Policies for Switching Bandit Problems (2011)Online portfolio selection (2014)Contributions to the theory of games. (1960)The Asymptotic Theory of Extreme Order Statistics (1990)Adaptive Game Playing Using Multiplicative Weights (1999)Efficient algorithms for online decision problems (2004)Some aspects of the sequential design of experiments (1952)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)A Tutorial on Thompson Sampling (2018)A unified framework for stochastic optimization (2018)Online Decision Making with High-Dimensional Covariates (2019)Finite-Time Analysis of Kernelised Contextual Bandits (2013)Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits (2015)From Ads to Interventions: Contextual Bandits in Mobile Health (2017)Survey on speech emotion recognition: Features, classification schemes, and databases (2010)Improved second-order bounds for prediction with expert advice (2006)Regret Minimization Under Partial Monitoring (2006)Online Markov Decision Processes (2009)Thompson Sampling for Contextual Bandits with Linear Payoffs (2012)Introduction to Multi-Armed Bandits (2019)
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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
  • 2011Improved Algorithms for Linear Stochastic Bandits860 cited
  • 1997How to use expert advice631 cited
  • 1998Tracking the Best Expert557 cited
  • 2014Learning to Optimize via Posterior Sampling494 cited
  • 2002Adaptive and self-confident on-line learning algorithms181 cited
  • 2010Contextual Multi-Armed Bandits175 cited
  • 2013Follow the Leader If You Can, Hedge If You Must92 cited
  • 2009A parameter-free hedging algorithm92 cited
  • 2015Distributed Online Learning via Cooperative Contextual Bandits53 cited

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