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Global optimization of Lipschitz functions
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Global optimization of Lipschitz functions (2017)Global optimization of Lipschitz functionsFrom Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planning (2014)From Bandits to Monte-Carlo T…BayesOpt: A Bayesian Optimization Library for Nonlinear Optimization, Experimental Design and Bandits (2014)BayesOpt: A Bayesian Optimiza…Multi-Modal Dynamic Pricing (2019)Multi-Modal Dynamic PricingFinite-time Analysis of the Multiarmed Bandit Problem (2002)The Nonstochastic Multiarmed Bandit Problem (2002)Prediction, Learning, and Games (2006)Matroid Bandits: Fast Combinatorial Optimization with Learning (2014)Optimal Best Arm Identification with Fixed Confidence (2016)Bandits and Experts in Metric Spaces (2019)Design and Analysis of Computer Experiments (1989)A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning (2010)Practical Bayesian Optimization of Machine Learning Algorithms (2012)GPflowOpt: A Bayesian Optimization Library using TensorFlow (2017)Practical Bayesian support vector regression for financial time series prediction and market condition change detection (2017)A Multi-Stage Self-Adaptive Classifier Ensemble Model With Application in Credit Scoring (2019)Using confidence bounds for exploitation-exploration trade-offs (2003)Multi‐Armed Bandit Allocation Indices (2011)Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization (2016)Bandit-based inventory optimisation: Reinforcement learning in multi-echelon supply chains (2022)
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References

  • 2014BayesOpt: A Bayesian Optimization Library for Nonlinear Optimization, Experimental Design and Bandits248 cited
  • 2014From Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planning233 cited

Cited by

  • 2019Multi-Modal Dynamic Pricing58 cited

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