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Achieving All with No Parameters: AdaNormalHedge
14 references·7 citing·34 second hop
Achieving All with No Parameters: AdaNormalHedge (2015)Achieving All with No Parameters: AdaNorm…From External to Internal Regret (2018)From External to Internal Reg…Online Optimization : Competing with Dynamic Comparators (2015)Online Optimization : Competi…A Second-order Bound with Excess Losses (2014)A Second-order Bound with Exc…Follow the Leader If You Can, Hedge If You Must (2013)Follow the Leader If You Can,…A parameter-free hedging algorithm (2009)A parameter-free hedging algo…Adaptive Algorithms for Online Decision Problems (2007)Adaptive Algorithms for Onlin…Prediction, Learning, and Games (2006)Prediction, Learning, and Gam…Tracking a Small Set of Experts by Mixing Past Posteriors (2001)Tracking a Small Set of Exper…Adaptive Game Playing Using Multiplicative Weights (1999)Adaptive Game Playing Using M…Tracking the Best Expert (1998)Tracking the Best ExpertA Game of Prediction with Expert Advice (1998)A Game of Prediction with Exp…Using and combining predictors that specialize (1997)Using and combining predictor…How 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…A theory of consciousness from a theoretical computer science perspective: Insights from the Conscious Turing Machine (2022)A theory of consciousness fro…Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach (2021)Non-stationary Reinforcement …Model selection for contextual bandits (2019)Model selection for contextua…Tracking the Best Expert in Non-stationary Stochastic Environments (2017)Tracking the Best Expert in N…Optimal learning with Bernstein online aggregation (2016)Optimal learning with Bernste…Efficient Algorithms for Adversarial Contextual Learning (2016)Efficient Algorithms for Adve…A Closer Look at Adaptive Regret (2012)A Closer Look at Adaptive Reg…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)Exponentiated Gradient versus Gradient Descent for Linear Predictors (1997)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)Efficient algorithms for online decision problems (2004)Contributions to the Theory of Games (1952)Theory of Games and Statistical Decisions. (1955)A General Class of Adaptive Strategies (2001)Nearly Tight Bounds for the Continuum-Armed Bandit Problem (2004)Stochastic Approximations and Differential Inclusions (2005)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)Competitive On‐line Statistics (2001)Encyclopedia of Statistical Sciences (2004)The Nonstochastic Multiarmed Bandit Problem (2002)Survey on speech emotion recognition: Features, classification schemes, and databases (2010)Averaging Expert Predictions (1999)Mortal Multi-Armed Bandits (2008)Regret bounds for sleeping experts and bandits (2010)Efficient learning algorithms for changing environments (2009)Learning Permutations with Exponential Weights (2009)Hedging structured concepts (2010)Regret Minimization Under Partial Monitoring (2006)Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret (2012)Moving average reversion strategy for on-line portfolio selection (2015)
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References

  • 1997A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting20,469 cited
  • 2006Prediction, Learning, and Games3,176 cited
  • 1997How to use expert advice631 cited
  • 1998Tracking the Best Expert557 cited
  • 1999Adaptive Game Playing Using Multiplicative Weights516 cited
  • 1998A Game of Prediction with Expert Advice280 cited
  • 1997Using and combining predictors that specialize237 cited
  • 2015Online Optimization : Competing with Dynamic Comparators175 cited
  • 2018From External to Internal Regret163 cited
  • 2001Tracking a Small Set of Experts by Mixing Past Posteriors124 cited
  • 2013Follow the Leader If You Can, Hedge If You Must92 cited
  • 2009A parameter-free hedging algorithm92 cited
  • 2014A Second-order Bound with Excess Losses67 cited
  • 2007Adaptive Algorithms for Online Decision Problems63 cited

Cited by

  • 2022A theory of consciousness from a theoretical computer science perspective: Insights from the Conscious Turing Machine69 cited
  • 2012A Closer Look at Adaptive Regret

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53 cited
  • 2016Optimal learning with Bernstein online aggregation52 cited
  • 2019Model selection for contextual bandits42 cited
  • 2016Efficient Algorithms for Adversarial Contextual Learning40 cited
  • 2017Tracking the Best Expert in Non-stationary Stochastic Environments32 cited
  • 2021Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach32 cited