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Tracking the Best Expert in Non-stationary Stochastic Environments
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Tracking the Best Expert in Non-stationary Stochastic Environments (2017)Tracking the Best Expert in Non-stationar…Online Optimization : Competing with Dynamic Comparators (2015)Online Optimization : Competi…Non-Stationary Stochastic Optimization (2015)Non-Stationary Stochastic Opt…Achieving All with No Parameters: AdaNormalHedge (2015)Achieving All with No Paramet…Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards (2014)Stochastic Multi-Armed-Bandit…A Second-order Bound with Excess Losses (2014)A Second-order Bound with Exc…Online Optimization with Gradual Variations (2012)Online Optimization with Grad…On Upper-Confidence Bound Policies for Switching Bandit Problems (2011)On Upper-Confidence Bound Pol…Exploration–exploitation tradeoff using variance estimates in multi-armed bandits (2009)Exploration–exploitation trad…Prediction, Learning, and Games (2006)Prediction, Learning, and Gam…The Nonstochastic Multiarmed Bandit Problem (2002)The Nonstochastic Multiarmed …Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach (2021)Non-stationary Reinforcement …A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)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)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)Some aspects of the sequential design of experiments (1952)Online convex programming and generalized infinitesimal gradient ascent (2003)Logarithmic regret algorithms for online convex optimization (2007)Adaptive Online Learning in Dynamic Environments (2018)Bandit Convex Optimization for Scalable and Dynamic IoT Management (2018)Optimal Exploration–Exploitation in a Multi-armed Bandit Problem with Non-stationary Rewards (2019)Multi-Armed Bandit Allocation Indices. (1990)The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond (2011)Intrinsic motivation, curiosity, and learning (2016)A Stochastic Approximation Method (1951)Robust Convex Optimization (1998)Online optimization in dynamic environments: Improved regret rates for strongly convex problems (2016)An Online Convex Optimization Approach to Proactive Network Resource Allocation (2017)Thompson Sampling: An Asymptotically Optimal Finite-Time Analysis (2012)Chasing Demand: Learning and Earning in a Changing Environment (2016)Time-Varying Gaussian Process Bandit Optimization (2016)A Change-Detection Based Framework for Piecewise-Stationary Multi-Armed Bandit Problem (2018)Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm (2014)Hedging the Drift: Learning to Optimize Under Non-Stationarity (2018)Online Learning: A Modern Introduction Using Convex Optimization (2019)Refined Lower Bounds for Adversarial Bandits (2016)
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References

  • 2006Prediction, Learning, and Games3,176 cited
  • 2002The Nonstochastic Multiarmed Bandit Problem2,210 cited
  • 2009Exploration–exploitation tradeoff using variance estimates in multi-armed bandits571 cited
  • 2011On Upper-Confidence Bound Policies for Switching Bandit Problems455 cited
  • 2015Non-Stationary Stochastic Optimization336 cited
  • 2014Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards193 cited
  • 2015Online Optimization : Competing with Dynamic Comparators175 cited
  • 2012Online Optimization with Gradual Variations133 cited
  • 2014A Second-order Bound with Excess Losses67 cited
  • 2015Achieving All with No Parameters: AdaNormalHedge54 cited

Cited by

  • 2021Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach32 cited

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