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Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits
16 references·4 citing·29 second hop
Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits (2023)Nearly Minimax-Optimal Regret for Linearl…Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits (2014)Taming the Monster: A Fast an…lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits (2013)lil' UCB : An Optimal Explora…Almost Optimal Exploration in Multi-Armed Bandits (2013)Almost Optimal Exploration in…Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)Regret Analysis of Stochastic…Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret (2012)Online Bandit Learning agains…Improved Algorithms for Linear Stochastic Bandits (2011)Improved Algorithms for Linea…Contextual Bandits with Linear Payoff Functions (2011)Contextual Bandits with Linea…UCB revisited: Improved regret bounds for the stochastic multi-armed bandit problem (2010)UCB revisited: Improved regre…Parametric Bandits: The Generalized Linear Case (2010)Parametric Bandits: The Gener…Linearly Parameterized Bandits (2010)Linearly Parameterized BanditsStochastic Linear Optimization Under Bandit Feedback (2008)Stochastic Linear Optimizatio…Using confidence bounds for exploitation-exploration trade-offs (2003)Using confidence bounds for e…Gambling in a rigged casino: The adversarial multi-armed bandit problem (2002)Gambling in a rigged casino: …Adaptive Treatment Allocation and the Multi-Armed Bandit Problem (1987)Adaptive Treatment Allocation…Information and information stability of random variables and processes (1964)Information and information s…Some aspects of the sequential design of experiments (1952)Some aspects of the sequentia…Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits Under Realizability (2021)Bypassing the Monster: A Fast…A Simple Approach for Non-stationary Linear Bandits (2021)A Simple Approach for Non-sta…Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes (2020)Nearly Minimax Optimal Reinfo…Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles (2020)Beyond UCB: Optimal and Effic…Finite-time Analysis of the Multiarmed Bandit Problem (2002)The Nonstochastic Multiarmed Bandit Problem (2002)Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms (2011)Thompson Sampling for Contextual Bandits with Linear Payoffs (2012)Collaborative Filtering Bandits (2016)A Stochastic Approximation Method (1951)Bandit Processes and Dynamic Allocation Indices (1979)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)An Empirical Evaluation of Thompson Sampling (2011)Bandits with Knapsacks (2013)Counterfactual Risk Minimization: Learning from Logged Bandit Feedback (2015)Fairness in Learning: Classic and Contextual Bandits (2016)Prediction, Learning, and Games (2006)Learning to Optimize via Posterior Sampling (2014)Multi-Armed Bandit Allocation Indices. (1990)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Adaptive Game Playing Using Multiplicative Weights (1999)Online convex optimization in the bandit setting: gradient descent without a gradient (2004)Multi-armed Bandit Algorithms and Empirical Evaluation (2005)Combinatorial Network Optimization With Unknown Variables: Multi-Armed Bandits With Linear Rewards and Individual Observations (2012)A Tutorial on Thompson Sampling (2018)Online Decision Making with High-Dimensional Covariates (2019)Information theoretic approximations for M/G/1 and G/G/1 queuing systems (1982)Game theory, maximum entropy, minimum discrepancy and robust Bayesian decision theory (2004)Making the Most of Your Samples (2015)Introduction to Multi-Armed Bandits (2019)Bandit Algorithms (2020)Information-seeking, curiosity, and attention: computational and neural mechanisms (2013)A unified framework for stochastic optimization (2018)
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References

  • 1952Some aspects of the sequential design of experiments2,183 cited
  • 2012Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems1,275 cited
  • 2003Using confidence bounds for exploitation-exploration trade-offs1,189 cited
  • 2011Improved Algorithms for Linear Stochastic Bandits860 cited
  • 1964Information and information stability of random variables and processes757 cited
  • 2002Gambling in a rigged casino: The adversarial multi-armed bandit problem741 cited
  • 2011Contextual Bandits with Linear Payoff Functions599 cited
  • 2008Stochastic Linear Optimization Under Bandit Feedback581 cited
  • 2010Linearly Parameterized Bandits428 cited
  • 2014Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits286 cited
  • 2010UCB revisited: Improved regret bounds for the stochastic multi-armed bandit problem285 cited
  • 1987Adaptive Treatment Allocation and the Multi-Armed Bandit Problem279 cited
  • 2013Almost Optimal Exploration in Multi-Armed Bandits258 cited
  • 2010Parametric Bandits: The Generalized Linear Case241 cited
  • 2013lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits196 cited

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  • 2012Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret121 cited
  • Cited by

    • 2020Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles75 cited
    • 2021Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits Under Realizability46 cited
    • 2021A Simple Approach for Non-stationary Linear Bandits40 cited
    • 2020Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes39 cited