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Online Optimization with Gradual Variations
6 references·8 citing·26 second hop
Online Optimization with Gradual Variations (2012)Online Optimization with Gradual Variatio…On the Universality of Online Mirror Descent (2011)On the Universality of Online…Logarithmic regret algorithms for online convex optimization (2007)Logarithmic regret algorithms…Prediction, Learning, and Games (2006)Prediction, Learning, and Gam…Improved second-order bounds for prediction with expert advice (2006)Improved second-order bounds …Online convex programming and generalized infinitesimal gradient ascent (2003)Online convex programming and…A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)A Decision-Theoretic Generali…Online Learning: A Modern Introduction Using Convex Optimization (2019)Online Learning: A Modern Int…Hedging the Drift: Learning to Optimize under Non-Stationarity (2019)Hedging the Drift: Learning t…Hedging the Drift: Learning to Optimize Under Non-Stationarity (2018)Hedging the Drift: Learning t…Tracking the Best Expert in Non-stationary Stochastic Environments (2017)Tracking the Best Expert in N…Efficient Algorithms for Adversarial Contextual Learning (2016)Efficient Algorithms for Adve…Accelerating Online Convex Optimization via Adaptive Prediction (2016)Accelerating Online Convex Op…Second-order Quantile Methods for Experts and Combinatorial Games (2015)Second-order Quantile Methods…Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm (2014)Adaptivity and Optimism: An I…Finite-time Analysis of the Multiarmed Bandit Problem (2002)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)The Nonstochastic Multiarmed Bandit Problem (2002)A parameter-free hedging algorithm (2009)Extracting certainty from uncertainty: regret bounded by variation in costs (2010)The best of both worlds: stochastic and adversarial bandits (2012)Exponentiated Gradient versus Gradient Descent for Linear Predictors (1997)Online Learning: Theory, Algorithms, and Applications (2007)Towards minimax policies for online linear optimization with bandit feedback (2012)A generalized online mirror descent with applications to classification and regression (2014)Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles (2020)The Theory of Learning in Games (1998)Ad click prediction (2013)Online Learning and Online Convex Optimization (2011)Model selection for contextual bandits (2019)An analog of the minimax theorem for vector payoffs (1956)Survey on speech emotion recognition: Features, classification schemes, and databases (2010)Non-Stationary Stochastic Optimization (2015)Introduction to Online Convex Optimization (2016)Introduction to Online Convex Optimization (2016)Multi-Armed Bandits with Fairness Constraints for Distributing Resources to Human Teammates (2020)Recent Advances in Reinforcement Learning in Finance (2021)The impact of renewable energy transition, green growth, green trade and green innovation on environmental quality: Evidence from top 10 green future countries (2023)Answering the Queen: Machine Learning and Financial Crises (2020)
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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
  • 2003Online convex programming and generalized infinitesimal gradient ascent1,733 cited
  • 2007Logarithmic regret algorithms for online convex optimization836 cited
  • 2006Improved second-order bounds for prediction with expert advice154 cited
  • 2011On the Universality of Online Mirror Descent139 cited

Cited by

  • 2019Online Learning: A Modern Introduction Using Convex Optimization111 cited
  • 2018Hedging the Drift: Learning to Optimize Under Non-Stationarity83 cited
  • 2014Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm46 cited
  • 2015Second-order Quantile Methods for Experts and Combinatorial Games42 cited
  • 2016Efficient Algorithms for Adversarial Contextual Learning40 cited
  • 2017Tracking the Best Expert in Non-stationary Stochastic Environments32 cited
  • 2016Accelerating Online Convex Optimization via Adaptive Prediction31 cited
  • 2019Hedging the Drift: Learning to Optimize under Non-Stationarity29 cited

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