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High-probability regret bounds for bandit online linear optimization
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High-probability regret bounds for bandit online linear optimization (2008)High-probability regret bounds for bandit…Stochastic Linear Optimization Under Bandit Feedback (2008)Stochastic Linear Optimizatio…Competing in the dark: An efficient algorithm for bandit linear optimization (2008)Competing in the dark: An eff…The Price of Bandit Information for Online Optimization (2007)The Price of Bandit Informati…The on-line shortest path problem under partial monitoring (2007)The on-line shortest path pro…Robbing the bandit: less regret in online geometric optimization against an adaptive adversary (2006)Robbing the bandit: less regr…Prediction, Learning, and Games (2006)Prediction, Learning, and Gam…Online Geometric Optimization in the Bandit Setting Against an Adaptive Adversary (2004)Online Geometric Optimization…Efficient algorithms for online decision problems (2004)Efficient algorithms for onli…Adaptive routing with end-to-end feedback (2004)Adaptive routing with end-to-…The Nonstochastic Multiarmed Bandit Problem (2002)The Nonstochastic Multiarmed …Explore no more: Improved high-probability regret bounds for non-stochastic bandits (2015)Explore no more: Improved hig…Characterizing Truthful Multi-armed Bandit Mechanisms (2014)Characterizing Truthful Multi…Contextual Bandit Learning with Predictable Rewards (2012)Contextual Bandit Learning wi…Non-Stochastic Bandit Slate Problems (2010)Non-Stochastic Bandit Slate P…Some aspects of the sequential design of experiments (1952)Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints (2011)Online Learning with Predictable Sequences (2012)The best of both worlds: stochastic and adversarial bandits (2012)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)Gambling in a rigged casino: The adversarial multi-armed bandit problem (2002)Online convex programming and generalized infinitesimal gradient ascent (2003)Adapting to a Changing Environment: the Brownian Restless Bandits. (2008)An analog of the minimax theorem for vector payoffs (1956)Combinatorial Bandits Revisited (2015)Minimal Exploration in Structured Stochastic Bandits (2017)Contributions to the theory of games. (1960)How to use expert advice (1997)Algorithms for portfolio management based on the Newton method (2006)Combinatorial bandits (2012)From Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planning (2014)Using confidence bounds for exploitation-exploration trade-offs (2003)Contextual Bandits with Linear Payoff Functions (2011)Thompson Sampling for Contextual Bandits with Linear Payoffs (2012)Learning to Optimize via Posterior Sampling (2014)Sleeping Experts and Bandits with Stochastic Action Availability and Adversarial Rewards (2009)Online Learning with Switching Costs and Other Adaptive Adversaries (2013)Learning, Regret Minimization, and Equilibria (2007)Online linear optimization and adaptive routing (2007)Introduction to Online Optimization (2011)Learning to Optimize via Information-Directed Sampling (2017)Distributed Bandit Online Convex Optimization With Time-Varying Coupled Inequality Constraints (2020)
this work references cited by second hop

References

  • 2006Prediction, Learning, and Games3,176 cited
  • 2002The Nonstochastic Multiarmed Bandit Problem2,210 cited
  • 2004Efficient algorithms for online decision problems595 cited
  • 2008Stochastic Linear Optimization Under Bandit Feedback581 cited
  • 2004Adaptive routing with end-to-end feedback190 cited
  • 2008Competing in the dark: An efficient algorithm for bandit linear optimization182 cited
  • 2004Online Geometric Optimization in the Bandit Setting Against an Adaptive Adversary172 cited
  • 2007The Price of Bandit Information for Online Optimization161 cited
  • 2007The on-line shortest path problem under partial monitoring151 cited
  • 2006Robbing the bandit: less regret in online geometric optimization against an adaptive adversary71 cited

Cited by

  • 2010Non-Stochastic Bandit Slate Problems61 cited
  • 2015Explore no more: Improved high-probability regret bounds for non-stochastic bandits61 cited
  • 2014Characterizing Truthful Multi-armed Bandit Mechanisms45 cited
  • 2012Contextual Bandit Learning with Predictable Rewards43 cited

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