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Tracking the Best Expert
3 references·16 citing·33 second hop
Tracking the Best Expert (1998)Tracking the Best ExpertHow to use expert advice (1997)How to use expert adviceExponentiated Gradient versus Gradient Descent for Linear Predictors (1997)Exponentiated Gradient versus…A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)A Decision-Theoretic Generali…Targeting Prospective Customers: Robustness of Machine-Learning Methods to Typical Data Challenges (2019)Targeting Prospective Custome…Automated Curriculum Learning for Neural Networks (2017)Automated Curriculum Learning…Online optimization in dynamic environments: Improved regret rates for strongly convex problems (2016)Online optimization in dynami…Online Convex Optimization in Dynamic Environments (2015)Online Convex Optimization in…Online portfolio selection (2014)Online portfolio selectionRegret in Online Combinatorial Optimization (2013)Regret in Online Combinatoria…On Upper-Confidence Bound Policies for Switching Bandit Problems (2011)On Upper-Confidence Bound Pol…On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems (2008)On Upper-Confidence Bound Pol…Mortal Multi-Armed Bandits (2008)Mortal Multi-Armed BanditsAdaptive combination of forecasts with application to wind energy (2008)Adaptive combination of forec…The on-line shortest path problem under partial monitoring (2007)The on-line shortest path pro…Adaptive and self-confident on-line learning algorithms (2002)Adaptive and self-confident o…Tracking a Small Set of Experts by Mixing Past Posteriors (2001)Tracking a Small Set of Exper…Competitive On‐line Statistics (2001)Competitive On‐line StatisticsA Game of Prediction with Expert Advice (1998)A Game of Prediction with Exp…Using and combining predictors that specialize (1997)Using and combining predictor…Finite-time Analysis of the Multiarmed Bandit Problem (2002)Prediction, Learning, and Games (2006)Thompson Sampling: An Asymptotically Optimal Finite-Time Analysis (2012)Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards (2014)Chasing Demand: Learning and Earning in a Changing Environment (2016)Relative Loss Bounds for On-Line Density Estimation with the Exponential Family of Distributions (2001)Bandit Convex Optimization for Scalable and Dynamic IoT Management (2018)Online Convex Optimization With Time-Varying Constraints and Bandit Feedback (2018)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)PORTFOLIO SELECTION* (1952)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Universal portfolios with and without transaction costs (1997)Moving average reversion strategy for on-line portfolio selection (2015)Robust Median Reversion Strategy for Online Portfolio Selection (2016)Gambling in a rigged casino: The adversarial multi-armed bandit problem (2002)Potential-Based Algorithms in On-Line Prediction and Game Theory (2003)A primal-dual perspective of online learning algorithms (2007)Online Learning: A Modern Introduction Using Convex Optimization (2019)Learning and development in neural networks: the importance of starting small (1993)The Nonstochastic Multiarmed Bandit Problem (2002)Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Curriculum Learning for Speech Emotion Recognition From Crowdsourced Labels (2019)Encyclopedia of Statistical Sciences (2004)Survey on speech emotion recognition: Features, classification schemes, and databases (2010)Averaging Expert Predictions (1999)Regret bounds for sleeping experts and bandits (2010)Online convex optimization in the bandit setting: gradient descent without a gradient (2004)Introduction to Online Convex Optimization (2016)Introduction to Online Convex Optimization (2016)
this work references cited by second hop

References

  • 1997A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting20,469 cited
  • 1997Exponentiated Gradient versus Gradient Descent for Linear Predictors856 cited
  • 1997How to use expert advice631 cited

Cited by

  • 2011On Upper-Confidence Bound Policies for Switching Bandit Problems455 cited
  • 1998A Game of Prediction with Expert Advice280 cited
  • 2014Online portfolio selection245 cited
  • 1997Using and combining predictors that specialize237 cited
  • 2017Automated Curriculum Learning for Neural Networks237 cited
  • 2001Competitive On‐line Statistics226 cited
  • 2015Online Convex Optimization in Dynamic Environments220 cited
  • 2013Regret in Online Combinatorial Optimization210 cited
  • 2016Online optimization in dynamic environments: Improved regret rates for strongly convex problems190 cited
  • 2002Adaptive and self-confident on-line learning algorithms181 cited
  • 2008On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems172 cited
  • 2007The on-line shortest path problem under partial monitoring151 cited

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2019
Targeting Prospective Customers: Robustness of Machine-Learning Methods to Typical Data Challenges
133 cited
  • 2001Tracking a Small Set of Experts by Mixing Past Posteriors124 cited
  • 2008Mortal Multi-Armed Bandits123 cited
  • 2008Adaptive combination of forecasts with application to wind energy111 cited