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Normal bandits of unknown means and variances
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Normal bandits of unknown means and variances (2017)Normal bandits of unknown means and varia…KULLBACK-LEIBLER UPPER CONFIDENCE BOUNDS FOR OPTIMAL SEQUENTIAL ALLOCATION (2013)KULLBACK-LEIBLER UPPER CONFID…The best of both worlds: stochastic and adversarial bandits (2012)The best of both worlds: stoc…An asymptotically optimal policy for finite support models in the multiarmed bandit problem (2011)An asymptotically optimal pol…UCB revisited: Improved regret bounds for the stochastic multi-armed bandit problem (2010)UCB revisited: Improved regre…An Asymptotically Optimal Bandit Algorithm for Bounded Support Models. (2010)An Asymptotically Optimal Ban…Exploration–exploitation tradeoff using variance estimates in multi-armed bandits (2009)Exploration–exploitation trad…Finite-time Analysis of the Multiarmed Bandit Problem (2002)Finite-time Analysis of the M…Optimal Adaptive Policies for Sequential Allocation Problems (1996)Optimal Adaptive Policies for…On the Gittins Index for Multiarmed Bandits (1992)On the Gittins Index for Mult…Multi-Armed Bandit Allocation Indices. (1990)Multi-Armed Bandit Allocation…Some aspects of the sequential design of experiments (1952)Some aspects of the sequentia…The Nonstochastic Multiarmed Bandit Problem (2002)A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences (2011)Minimal Exploration in Structured Stochastic Bandits (2017)On Bayesian index policies for sequential resource allocation (2018)Bandit Problems, Sequential Allocation of Experiments. (1987)The Multi-Armed Bandit Problem: Decomposition and Computation (1987)On Bayesian Upper Confidence Bounds for Bandit Problems (2012)Kullback–Leibler upper confidence bounds for optimal sequential allocation (2013)A Stochastic Approximation Method (1951)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Prediction, Learning, and Games (2006)One Practical Algorithm for Both Stochastic and Adversarial Bandits (2014)Bandits with unobserved confounders: a causal approach (2015)The non-stationary stochastic multi-armed bandit problem (2017)Bandit Processes and Dynamic Allocation Indices (1979)From Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planning (2014)Batched bandit problems (2016)Explore First, Exploit Next: The True Shape of Regret in Bandit Problems (2016)The multi-armed bandit problem with covariates (2011)Almost Optimal Exploration in Multi-Armed Bandits (2013)Multi-Armed Bandit Problems (2007)Multi-armed Bandit Models for the Optimal Design of Clinical Trials: Benefits and Challenges (2015)The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond (2011)Thompson Sampling: An Asymptotically Optimal Finite-Time Analysis (2012)Intrinsic motivation, curiosity, and learning (2016)Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)An Empirical Evaluation of Thompson Sampling (2011)Analysis of Thompson Sampling for the multi-armed bandit problem (2011)Introduction to Multi-Armed Bandits (2019)
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References

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  • 1952Some aspects of the sequential design of experiments2,183 cited
  • 1990Multi-Armed Bandit Allocation Indices.997 cited
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  • 1992On the Gittins Index for Multiarmed Bandits259 cited
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  • 2010An Asymptotically Optimal Bandit Algorithm for Bounded Support Models.139 cited
  • 2011An asymptotically optimal policy for finite support models in the multiarmed bandit problem94 cited

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