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Follow the Leader If You Can, Hedge If You Must
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Follow the Leader If You Can, Hedge If You Must (2013)Follow the Leader If You Can, Hedge If Yo…THE META-INDUCTIVE JUSTIFICATION OF INDUCTION (2019)THE META-INDUCTIVE JUSTIFICAT…Non-Asymptotic Pure Exploration by Solving Games (2019)Non-Asymptotic Pure Explorati…Ambiguity, Robust Statistics, and Raiffa's Critique (2019)Ambiguity, Robust Statistics,…Scale-free online learning (2017)Scale-free online learningRefined Lower Bounds for Adversarial Bandits (2016)Refined Lower Bounds for Adve…Second-order Quantile Methods for Experts and Combinatorial Games (2015)Second-order Quantile Methods…Achieving All with No Parameters: AdaNormalHedge (2015)Achieving All with No Paramet…One Practical Algorithm for Both Stochastic and Adversarial Bandits (2014)One Practical Algorithm for B…Follow the Leader with Dropout Perturbations (2014)Follow the Leader with Dropou…Exploiting easy data in online optimization (2014)Exploiting easy data in onlin…Finite-time Analysis of the Multiarmed Bandit Problem (2002)The Nonstochastic Multiarmed Bandit Problem (2002)Prediction, Learning, and Games (2006)Taming Non-stationary Bandits: A Bayesian Approach (2017)The non-stationary stochastic multi-armed bandit problem (2017)Adversarial Bandits with Knapsacks (2019)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)How to use expert advice (1997)A Closer Look at Adaptive Regret (2012)Optimal learning with Bernstein online aggregation (2016)A theory of consciousness from a theoretical computer science perspective: Insights from the Conscious Turing Machine (2022)Online Learning and Online Convex Optimization (2011)Online convex programming and generalized infinitesimal gradient ascent (2003)Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Online Learning Algorithms (2020)Gambling in a rigged casino: The adversarial multi-armed bandit problem (2002)Minimax policies for adversarial and stochastic bandits (2004)Fact, Fiction, and Forecast. (1955)The Metainductive Justification of Induction: The Pool of Strategies (2019)Optimality Justifications (2024)On the Complexity of Best Arm Identification in Multi-Armed Bandit Models (2014)Maxmin expected utility with non-unique prior (1989)A Smooth Model of Decision Making under Ambiguity (2005)Ambiguity Aversion, Robustness, and the Variational Representation of Preferences (2006)Model selection for contextual bandits (2019)
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  • 2019Non-Asymptotic Pure Exploration by Solving Games76 cited
  • 2014One Practical Algorithm for Both Stochastic and Adversarial Bandits74 cited
  • 2016Refined Lower Bounds for Adversarial Bandits59 cited
  • 2015Achieving All with No Parameters: AdaNormalHedge54 cited
  • 2017Scale-free online learning48 cited
  • 2015Second-order Quantile Methods for Experts and Combinatorial Games42 cited
  • 2014Follow the Leader with Dropout Perturbations39 cited
  • 2014Exploiting easy data in online optimization37 cited
  • 2019THE META-INDUCTIVE JUSTIFICATION OF INDUCTION32 cited
  • 2019Ambiguity, Robust Statistics, and Raiffa's Critique1 cited

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