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Bandits for Taxonomies: A Model-based Approach
6 references·7 citing·33 second hop
Bandits for Taxonomies: A Model-based Approach (2007)Bandits for Taxonomies: A Model-based App…Bandit problems with side observations (2005)Bandit problems with side obs…Finite-time Analysis of the Multiarmed Bandit Problem (2002)Finite-time Analysis of the M…Bandit Problems, Sequential Allocation of Experiments. (1987)Bandit Problems, Sequential A…Adaptive Treatment Allocation and the Multi-Armed Bandit Problem (1987)Adaptive Treatment Allocation…Bandit Processes and Dynamic Allocation Indices (1979)Bandit Processes and Dynamic …A One-Armed Bandit Problem with a Concomitant Variable (1979)A One-Armed Bandit Problem wi…Novel pricing strategies for revenue maximization and demand learning using an exploration–exploitation framework (2021)Novel pricing strategies for …Bandits and Experts in Metric Spaces (2019)Bandits and Experts in Metric…Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems (2016)Adaptive Contract Design for …Learning to Rank (2015)Learning to RankRanked bandits in metric spaces: learning diverse rankings over large document collections (2013)Ranked bandits in metric spac…Hierarchical Exploration for Accelerating Contextual Bandits (2012)Hierarchical Exploration for …Multi-armed bandits on implicit metric spaces (2011)Multi-armed bandits on implic…The Nonstochastic Multiarmed Bandit Problem (2002)Prediction, Learning, and Games (2006)Online Stochastic Optimization under Correlated Bandit Feedback (2014)Multi-Armed Bandits: Theory and Applications to Online Learning in Networks (2019)Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles (2020)A Bayes Sequential Sampling Inspection Plan (1965)Randomized Allocation with nonparametric estimation for a multi-armed bandit problem with covariates (2002)A Linear Response Bandit Problem (2013)Some aspects of the sequential design of experiments (1952)Asymptotically efficient allocation rules for the multiarmed bandit problem with multiple plays-Part I: I.I.D. rewards (1987)Exploration scavenging (2008)Multiclass classification with bandit feedback using adaptive regularization (2012)The multi-armed bandit problem with covariates (2013)The Theory of Incentives: The Principal-Agent Model (2001)A Perspective on Incentive Design: Challenges and Opportunities (2018)Simple versus Optimal Contracts (2019)Bayesian Exploration: Incentivizing Exploration in Bayesian Games (2021)Applied Statistical Decision Theory (1962)Applied Statistical Decision Theory. (1962)Restless bandits: activity allocation in a changing world (1988)Legislative leviathan: party government in the House (1993)Optimal Adaptive Policies for Sequential Allocation Problems (1996)On Bayesian Upper Confidence Bounds for Bandit Problems (2012)Customer Acquisition via Display Advertising Using Multi-Armed Bandit Experiments (2017)Learning by Doing and the Choice of Technology (1996)Linearly Parameterized Bandits (2010)Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms (2011)DCM Bandits: Learning to Rank with Multiple Clicks (2016)Multi-Objective Ranked Bandits for Recommender Systems (2017)Online Learning to Rank in Stochastic Click Models (2017)Contextual Pricing for Lipschitz Buyers (2018)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)
this work references cited by second hop

References

  • 2002Finite-time Analysis of the Multiarmed Bandit Problem5,980 cited
  • 1979Bandit Processes and Dynamic Allocation Indices1,488 cited
  • 1987Bandit Problems, Sequential Allocation of Experiments.566 cited
  • 1987Adaptive Treatment Allocation and the Multi-Armed Bandit Problem279 cited
  • 2005Bandit problems with side observations129 cited
  • 1979A One-Armed Bandit Problem with a Concomitant Variable107 cited

Cited by

  • 2019Bandits and Experts in Metric Spaces75 cited
  • 2016Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems75 cited
  • 2013Ranked bandits in metric spaces: learning diverse rankings over large document collections63 cited
  • 2011Multi-armed bandits on implicit metric spaces40 cited
  • 2012Hierarchical Exploration for Accelerating Contextual Bandits31 cited
  • 2015Learning to Rank30 cited
  • 2021Novel pricing strategies for revenue maximization and demand learning using an exploration–exploitation framework13 cited

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