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Tighter Bounds for Multi-Armed Bandits with Expert Advice
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Tighter Bounds for Multi-Armed Bandits with Expert Advice (2009)Tighter Bounds for Multi-Armed Bandits wi…Mortal Multi-Armed Bandits (2008)Mortal Multi-Armed BanditsThe Price of Bandit Information for Online Optimization (2007)The Price of Bandit Informati…The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information (2007)The Epoch-Greedy Algorithm fo…Prediction, Learning, and Games (2006)Prediction, Learning, and Gam…The Nonstochastic Multiarmed Bandit Problem (2002)The Nonstochastic Multiarmed …A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)A Decision-Theoretic Generali…Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits Under Realizability (2021)Bypassing the Monster: A Fast…BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits (2016)BISTRO: An Efficient Relaxati…Explore no more: Improved high-probability regret bounds for non-stochastic bandits (2015)Explore no more: Improved hig…Resourceful Contextual Bandits (2014)Resourceful Contextual BanditsMulti-Armed Bandit Allocation Indices. (1990)Dynamic Pricing Without Knowing the Demand Function: Risk Bounds and Near-Optimal Algorithms (2009)Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits (2015)An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives (2015)Linear Contextual Bandits with Knapsacks (2015)Finite-time Analysis of the Multiarmed Bandit Problem (2002)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)Some aspects of the sequential design of experiments (1952)Gambling in a rigged casino: The adversarial multi-armed bandit problem (2002)Parametric Bandits: The Generalized Linear Case (2010)Online Decision Making with High-Dimensional Covariates (2019)Survey on Applications of Multi-Armed and Contextual Bandits (2020)Using confidence bounds for exploitation-exploration trade-offs (2003)Explore/Exploit Schemes for Web Content Optimization (2009)Multi-Armed Bandit with Budget Constraint and Variable Costs (2013)Bandits with concave rewards and convex knapsacks (2014)Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits (2014)Efficient Algorithms for Adversarial Contextual Learning (2016)Thompson Sampling for Online Personalized Assortment Optimization Problems with Multinomial Logit Choice Models (2017)A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal, and Parameter-free (2019)An Empirical Evaluation of Thompson Sampling (2011)Bandit Algorithms (2020)Survey on speech emotion recognition: Features, classification schemes, and databases (2010)Introduction to Online Optimization (2011)Learning to Optimize via Information-Directed Sampling (2017)Distributed Bandit Online Convex Optimization With Time-Varying Coupled Inequality Constraints (2020)Refined Lower Bounds for Adversarial Bandits (2016)Taming Non-stationary Bandits: A Bayesian Approach (2017)The non-stationary stochastic multi-armed bandit problem (2017)
this work references cited by second hop

References

  • 1997A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting20,469 cited
  • 2006Prediction, Learning, and Games3,176 cited
  • 2002The Nonstochastic Multiarmed Bandit Problem2,210 cited
  • 2007The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information426 cited
  • 2007The Price of Bandit Information for Online Optimization161 cited
  • 2008Mortal Multi-Armed Bandits123 cited

Cited by

  • 2014Resourceful Contextual Bandits75 cited
  • 2016BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits70 cited
  • 2015Explore no more: Improved high-probability regret bounds for non-stochastic bandits61 cited
  • 2021Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits Under Realizability46 cited

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