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Transferable Contextual Bandit for Cross-Domain Recommendation
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Transferable Contextual Bandit for Cross-Domain Recommendation (2018)Transferable Contextual Bandit for Cross-…Factorization Bandits for Interactive Recommendation (2017)Factorization Bandits for Int…Learning Hidden Features for Contextual Bandits (2016)Learning Hidden Features for …Collaborative Filtering Bandits (2016)Collaborative Filtering Bandi…A Survey on Contextual Multi-armed Bandits (2015)A Survey on Contextual Multi-…A Survey of Online Experiment Design with the Stochastic Multi-Armed Bandit (2015)A Survey of Online Experiment…Thompson Sampling for Contextual Bandits with Linear Payoffs (2012)Thompson Sampling for Context…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 Bandits with Linear Payoff Functions (2011)Contextual Bandits with Linea…Epsilon–First Policies for Budget–Limited Multi-Armed Bandits (2010)Epsilon–First Policies for Bu…Using confidence bounds for exploitation-exploration trade-offs (2003)Using confidence bounds for e…Finite-time Analysis of the Multiarmed Bandit Problem (2002)The Nonstochastic Multiarmed Bandit Problem (2002)Stochastic Linear Optimization Under Bandit Feedback (2008)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits (2015)Continuous multi-task Bayesian Optimisation with correlation (2018)Some aspects of the sequential design of experiments (1952)Introduction to Multi-Armed Bandits (2019)Bandit Algorithms (2020)Prediction, Learning, and Games (2006)Learning to Optimize via Posterior Sampling (2014)An Empirical Evaluation of Thompson Sampling (2011)Further Optimal Regret Bounds for Thompson Sampling (2012)A Tutorial on Thompson Sampling (2018)On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems (2008)Algorithms for multi-armed bandit problems (2014)Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits (2014)Reinforcement Mechanism Design for e-commerce (2018)Multi-Armed Bandits with Fairness Constraints for Distributing Resources to Human Teammates (2020)Some Aspects of the Sequential Design of Experiments (1985)Multi-Armed Bandit with Budget Constraint and Variable Costs (2013)Bandits with concave rewards and convex knapsacks (2014)Efficient crowdsourcing of unknown experts using bounded multi-armed bandits (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)Learning Contextual Bandits in a Non-stationary Environment (2018)Distributed Clustering of Linear Bandits in Peer to Peer Networks (2016)A Change-Detection Based Framework for Piecewise-Stationary Multi-Armed Bandit Problem (2018)
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References

  • 2003Using confidence bounds for exploitation-exploration trade-offs1,189 cited
  • 2011Improved Algorithms for Linear Stochastic Bandits860 cited
  • 2012Thompson Sampling for Contextual Bandits with Linear Payoffs600 cited
  • 2011Contextual Bandits with Linear Payoff Functions599 cited
  • 2011Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms448 cited
  • 2016Collaborative Filtering Bandits291 cited
  • 2010Epsilon–First Policies for Budget–Limited Multi-Armed Bandits140 cited
  • 2017Factorization Bandits for Interactive Recommendation94 cited
  • 2015A Survey on Contextual Multi-armed Bandits87 cited
  • 2015A Survey of Online Experiment Design with the Stochastic Multi-Armed Bandit87 cited
  • 2016Learning Hidden Features for Contextual Bandits79 cited

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