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Decentralized Online Learning: Take Benefits from Others’ Data without Sharing Your Own to Track Global Trend
16 references·0 citing·28 second hopsampled
Decentralized Online Learning: Take Benefits from Others’ Data without Sharing Your Own to Track Global Trend (2022)Decentralized Online Learning: Take Benef…Adaptive Online Learning in Dynamic Environments (2018)Adaptive Online Learning in D…Dynamic Regret of Strongly Adaptive Methods (2017)Dynamic Regret of Strongly Ad…Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient (2016)Tracking Slowly Moving Clairv…Online optimization in dynamic environments: Improved regret rates for strongly convex problems (2016)Online optimization in dynami…Introduction to Online Convex Optimization (2016)Introduction to Online Convex…Introduction to Online Convex Optimization (2016)Introduction to Online Convex…Improved Dynamic Regret for Non-degenerate Functions (2016)Improved Dynamic Regret for N…Online Optimization : Competing with Dynamic Comparators (2015)Online Optimization : Competi…Online Convex Optimization in Dynamic Environments (2015)Online Convex Optimization in…Online Learning and Online Convex Optimization (2012)Online Learning and Online Co…Mirror Descent Meets Fixed Share (and feels no regret) (2012)Mirror Descent Meets Fixed Sh…A Closer Look at Adaptive Regret (2012)A Closer Look at Adaptive Reg…Online Learning and Online Convex Optimization (2011)Online Learning and Online Co…Introduction to Online Optimization (2011)Introduction to Online Optimi…Online convex programming and generalized infinitesimal gradient ascent (2003)Online convex programming and…Tracking the Best Expert (1998)Tracking the Best ExpertA Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Exponentiated Gradient versus Gradient Descent for Linear Predictors (1997)How to use expert advice (1997)Using confidence bounds for exploitation-exploration trade-offs (2003)Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Relative Loss Bounds for On-Line Density Estimation with the Exponential Family of Distributions (2001)Prediction, Learning, and Games (2006)Bandit Convex Optimization for Scalable and Dynamic IoT Management (2018)Online Convex Optimization With Time-Varying Constraints and Bandit Feedback (2018)Some aspects of the sequential design of experiments (1952)The Nonstochastic Multiarmed Bandit Problem (2002)Big Data Deep Learning: Challenges and Perspectives (2014)A survey of machine learning for big data processing (2016)A survey on deep learning for big data (2017)Logarithmic regret algorithms for online convex optimization (2007)Optimal Exploration–Exploitation in a Multi-armed Bandit Problem with Non-stationary Rewards (2019)The Theory of Learning in Games (1998)A Simple Adaptive Procedure Leading to Correlated Equilibrium (2000)The Pricing of Options and Corporate Liabilities (1973)An Online Convex Optimization Approach to Proactive Network Resource Allocation (2017)A Marketplace for Data (2019)Introduction to Multi-Armed Bandits (2019)Theory of games and economic behavior (2019)A Stochastic Approximation Method (1951)Finite-time Analysis of the Multiarmed Bandit Problem (2002)Towards minimax policies for online linear optimization with bandit feedback (2012)Stochastic online optimization. Single-point and multi-point non-linear multi-armed bandits. Convex and strongly-convex case (2017)Bandit Algorithms (2020)
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References

  • 2003Online convex programming and generalized infinitesimal gradient ascent1,789 cited
  • 2012Online Learning and Online Convex Optimization1,265 cited
  • 2011Online Learning and Online Convex Optimization1,170 cited
  • 2016Introduction to Online Convex Optimization893 cited
  • 2016Introduction to Online Convex Optimization839 cited
  • 1998Tracking the Best Expert559 cited
  • 2015Online Convex Optimization in Dynamic Environments220 cited
  • 2016Online optimization in dynamic environments: Improved regret rates for strongly convex problems190 cited
  • 2015Online Optimization : Competing with Dynamic Comparators175 cited
  • 2011Introduction to Online Optimization108 cited
  • 2018Adaptive Online Learning in Dynamic Environments89 cited
  • 2016Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient84 cited
  • 2016Improved Dynamic Regret for Non-degenerate Functions80 cited
  • 2017Dynamic Regret of Strongly Adaptive Methods56 cited
  • 2012A Closer Look at Adaptive Regret53 cited
  • 2012Mirror Descent Meets Fixed Share (and feels no regret)

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