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Linear Contextual Bandits with Knapsacks
8 references·8 citing·31 second hop
Linear Contextual Bandits with Knapsacks (2015)Linear Contextual Bandits with KnapsacksTaming the Monster: A Fast and Simple Algorithm for Contextual Bandits (2014)Taming the Monster: A Fast an…Resourceful Contextual Bandits (2014)Resourceful Contextual BanditsBandits with concave rewards and convex knapsacks (2014)Bandits with concave rewards …Bandits with Knapsacks (2013)Bandits with KnapsacksImproved Algorithms for Linear Stochastic Bandits (2011)Improved Algorithms for Linea…Contextual Bandits with Linear Payoff Functions (2011)Contextual Bandits with Linea…Stochastic Linear Optimization Under Bandit Feedback (2008)Stochastic Linear Optimizatio…Using confidence bounds for exploitation-exploration trade-offs (2003)Using confidence bounds for e…Dynamic Pricing with Fairness Constraints (2021)Dynamic Pricing with Fairness…Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits Under Realizability (2021)Bypassing the Monster: A Fast…Robust Dynamic Pricing with Demand Learning in the Presence of Outlier Customers (2020)Robust Dynamic Pricing with D…Linear Stochastic Bandits Under Safety Constraints (2019)Linear Stochastic Bandits Und…Incorporating Behavioral Constraints in Online AI Systems (2019)Incorporating Behavioral Cons…Adversarial Bandits with Knapsacks (2019)Adversarial Bandits with Knap…Using Contextual Bandits with Behavioral Constraints for Constrained Online Movie Recommendation (2018)Using Contextual Bandits with…Fair Personalization (2017)Fair PersonalizationMulti-Armed Bandit Allocation Indices. (1990)The Nonstochastic Multiarmed Bandit Problem (2002)Dynamic Pricing Without Knowing the Demand Function: Risk Bounds and Near-Optimal Algorithms (2009)Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits (2015)An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives (2015)Feature-based Dynamic Pricing (2016)Finite-time Analysis of the Multiarmed Bandit Problem (2002)Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms (2011)Collaborative Filtering Bandits (2016)A desicion-theoretic generalization of on-line learning and an application to boosting (1995)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems (2016)Dynamic Pricing in High-Dimensions (2016)Bandits and Experts in Metric Spaces (2019)An Empirical Evaluation of Thompson Sampling (2011)Counterfactual Risk Minimization: Learning from Logged Bandit Feedback (2015)Fairness in Learning: Classic and Contextual Bandits (2016)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)Thompson Sampling for Contextual Bandits with Linear Payoffs (2012)Moral control and ownership in AI systems (2020)Using the Crowd to Prevent Harmful AI Behavior (2020)The social dilemma of autonomous vehicles (2016)Axies: Identifying and Evaluating Context-Specific Values (2021)What values should an agent align with? (2022)Aggregating value systems for decision support (2024)Learning in Repeated Auctions with Budgets: Regret Minimization and Equilibrium (2017)Bandits with Knapsacks (2018)
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References

  • 2003Using confidence bounds for exploitation-exploration trade-offs1,189 cited
  • 2011Improved Algorithms for Linear Stochastic Bandits860 cited
  • 2011Contextual Bandits with Linear Payoff Functions599 cited
  • 2008Stochastic Linear Optimization Under Bandit Feedback581 cited
  • 2014Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits286 cited
  • 2013Bandits with Knapsacks211 cited
  • 2014Bandits with concave rewards and convex knapsacks122 cited
  • 2014Resourceful Contextual Bandits75 cited

Cited by

  • 2019Incorporating Behavioral Constraints in Online AI Systems59 cited
  • 2018Using Contextual Bandits with Behavioral Constraints for Constrained Online Movie Recommendation46 cited
  • 2021Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits Under Realizability46 cited
  • 2019Linear Stochastic Bandits Under Safety Constraints43 cited
  • 2019Adversarial Bandits with Knapsacks42 cited
  • 2017Fair Personalization28 cited
  • 2020Robust Dynamic Pricing with Demand Learning in the Presence of Outlier Customers18 cited

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2021
Dynamic Pricing with Fairness Constraints
18 cited