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ε-first policies for budget-limited multi-armed bandits
5 references·6 citing·34 second hop
ε-first policies for budget-limited multi-armed bandits (2010)ε-first policies for budget-limited multi…Pure Exploration in Multi-armed Bandits Problems (2009)Pure Exploration in Multi-arm…Approximation algorithms for budgeted learning problems (2007)Approximation algorithms for …The max K-armed bandit: a new model of exploration applied to search heuristic selection (2005)The max K-armed bandit: a new…Finite-time Analysis of the Multiarmed Bandit Problem (2002)Finite-time Analysis of the M…Some aspects of the sequential design of experiments (1952)Some aspects of the sequentia…Adversarial Bandits with Knapsacks (2019)Adversarial Bandits with Knap…Thompson Sampling for Budgeted Multi-armed Bandits (2015)Thompson Sampling for Budgete…An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives (2015)An efficient algorithm for co…Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits (2015)Algorithms with Logarithmic o…Resourceful Contextual Bandits (2014)Resourceful Contextual BanditsEfficient Crowdsourcing of Unknown Experts using Multi-Armed Bandits (2012)Efficient Crowdsourcing of Un…Multi-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)Linear Contextual Bandits with Knapsacks (2015)Multi-armed Bandit Algorithms and Empirical Evaluation (2005)Financial incentives and the "performance of crowds" (2009)Epsilon–First Policies for Budget–Limited Multi-Armed Bandits (2010)A Truthful Budget Feasible Multi-Armed Bandit Mechanism for Crowdsourcing Time Critical Tasks (2015)An Introduction to Statistical Modeling of Extreme Values (2001)An asymptotically optimal algorithm for the max k-armed bandit problem (2006)Learning dynamic algorithm portfolios (2007)Efficient Multi-Start Strategies for Local Search Algorithms (2011)An Empirical Evaluation of Thompson Sampling (2011)Analysis of Thompson Sampling for the multi-armed bandit problem (2011)A Combinatorial-Bandit Algorithm for the Online Joint Bid/Budget Optimization of Pay-per-Click Advertising Campaigns (2018)The Epoch-Greedy algorithm for contextual multi-armed bandits (2007)The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond (2011)Using Contextual Bandits with Behavioral Constraints for Constrained Online Movie Recommendation (2018)Incorporating Behavioral Constraints in Online AI Systems (2019)A Stochastic Approximation Method (1951)Bandit Processes and Dynamic Allocation Indices (1979)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Restless bandits: activity allocation in a changing world (1988)Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)The Sample Average Approximation Method for Stochastic Discrete Optimization (2002)Paradoxes in Learning and the Marginal Value of Information (2010)Contextual Bandits with Linear Payoff Functions (2011)Improved Algorithms for Linear Stochastic Bandits (2011)Learning to Be Fair: A Consequentialist Approach to Equitable Decision Making (2024)Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization (2012)Almost Optimal Exploration in Multi-Armed Bandits (2013)Non-stochastic Best Arm Identification and Hyperparameter Optimization (2015)Prediction, Learning, and Games (2006)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
  • 1952Some aspects of the sequential design of experiments2,183 cited
  • 2009Pure Exploration in Multi-armed Bandits Problems365 cited
  • 2005The max K-armed bandit: a new model of exploration applied to search heuristic selection114 cited
  • 2007Approximation algorithms for budgeted learning problems85 cited

Cited by

  • 2012Efficient Crowdsourcing of Unknown Experts using Multi-Armed Bandits78 cited
  • 2014Resourceful Contextual Bandits75 cited
  • 2015Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits61 cited
  • 2015Thompson Sampling for Budgeted Multi-armed Bandits47 cited
  • 2015An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives46 cited
  • 2019Adversarial Bandits with Knapsacks42 cited

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