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Latent Bandits.
11 references·2 citing·36 second hop
Latent Bandits. (2014)Latent Bandits.KULLBACK-LEIBLER UPPER CONFIDENCE BOUNDS FOR OPTIMAL SEQUENTIAL ALLOCATION (2013)KULLBACK-LEIBLER UPPER CONFID…Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms (2011)Unbiased offline evaluation o…Improved Algorithms for Linear Stochastic Bandits (2011)Improved Algorithms for Linea…Contextual Multi-Armed Bandits (2010)Contextual Multi-Armed BanditsStochastic Linear Optimization Under Bandit Feedback (2008)Stochastic Linear Optimizatio…On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems (2008)On Upper-Confidence Bound Pol…The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information (2007)The Epoch-Greedy Algorithm fo…The Epoch-Greedy algorithm for contextual multi-armed bandits (2007)The Epoch-Greedy algorithm fo…Online Learning with Prior Knowledge (2007)Online Learning with Prior Kn…Using confidence bounds for exploitation-exploration trade-offs (2003)Using confidence bounds for e…Asymptotically efficient adaptive allocation schemes for controlled i.i.d. processes: finite parameter space (1989)Asymptotically efficient adap…Optimal Exploitation of Clustering and History Information in Multi-armed Bandit (2019)Optimal Exploitation of Clust…Latent Contextual Bandits and their Application to Personalized Recommendations for New Users (2016)Latent Contextual Bandits and…Finite-time Analysis of the Multiarmed Bandit Problem (2002)The Nonstochastic Multiarmed Bandit Problem (2002)Prediction, Learning, and Games (2006)Finite-Time Analysis of Kernelised Contextual Bandits (2013)Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits (2015)From Ads to Interventions: Contextual Bandits in Mobile Health (2017)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms (2014)A Survey of Online Experiment Design with the Stochastic Multi-Armed Bandit (2015)A Change-Detection Based Framework for Piecewise-Stationary Multi-Armed Bandit Problem (2018)An Asymptotic Minimax Theorem for the Two Armed Bandit Problem (1960)Asymptotically efficient allocation rules for the multiarmed bandit problem with multiple plays-Part I: I.I.D. rewards (1987)Asymptotically efficient adaptive allocation rules for the multiarmed bandit problem with switching cost (1988)Bounded regret in stochastic multi-armed bandits (2013)DCM Bandits: Learning to Rank with Multiple Clicks (2016)Some aspects of the sequential design of experiments (1952)Introduction to Multi-Armed Bandits (2019)Bandit Algorithms (2020)Gambling in a rigged casino: The adversarial multi-armed bandit problem (2002)Parametric Bandits: The Generalized Linear Case (2010)Online Decision Making with High-Dimensional Covariates (2019)Survey on Applications of Multi-Armed and Contextual Bandits (2020)Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems (2006)Interactively optimizing information retrieval systems as a dueling bandits problem (2009)Contextual Gaussian Process Bandit Optimization (2011)Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits (2014)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)Thompson Sampling for Contextual Bandits with Linear Payoffs (2012)Learning to Optimize via Posterior Sampling (2014)Contextual Bandits with Similarity Information (2009)Optimistic bayesian sampling in contextual-bandit problems (2012)Batch learning from logged bandit feedback through counterfactual risk minimization (2015)Contextual Bandits with Linear Payoff Functions (2011)
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References

  • 2003Using confidence bounds for exploitation-exploration trade-offs1,189 cited
  • 2011Improved Algorithms for Linear Stochastic Bandits860 cited
  • 2008Stochastic Linear Optimization Under Bandit Feedback581 cited
  • 2011Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms448 cited
  • 2007The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information426 cited
  • 2007The Epoch-Greedy algorithm for contextual multi-armed bandits307 cited
  • 2013KULLBACK-LEIBLER UPPER CONFIDENCE BOUNDS FOR OPTIMAL SEQUENTIAL ALLOCATION274 cited
  • 2010Contextual Multi-Armed Bandits175 cited
  • 2008On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems172 cited
  • 1989Asymptotically efficient adaptive allocation schemes for controlled i.i.d. processes: finite parameter space54 cited
  • 2007Online Learning with Prior Knowledge47 cited

Cited by

  • 2019Optimal Exploitation of Clustering and History Information in Multi-armed Bandit32 cited
  • 2016Latent Contextual Bandits and their Application to Personalized Recommendations for New Users31 cited

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