Exotic Bayesian Optimization
暂无分享,去创建一个
[1] Céline Helbert,et al. Gaussian process optimization with failures: classification and convergence proof , 2020, Journal of Global Optimization.
[2] Xuan Zeng,et al. An Efficient Multi-fidelity Bayesian Optimization Approach for Analog Circuit Synthesis , 2019, 2019 56th ACM/IEEE Design Automation Conference (DAC).
[3] Francesco Archetti,et al. Tuning hyperparameters of a SVM-based water demand forecasting system through parallel global optimization , 2019, Comput. Oper. Res..
[4] Francesco Archetti,et al. Optimizing Partially Defined Black-Box Functions Under Unknown Constraints via Sequential Model Based Optimization: An Application to Pump Scheduling Optimization in Water Distribution Networks , 2019, LION.
[5] A. Zilinskas,et al. On efficiency of bicriteria optimization , 2019 .
[6] Francesco Archetti,et al. Sequential model based optimization with black-box constraints: Feasibility determination via machine learning , 2019 .
[7] Guilherme Ottoni,et al. Constrained Bayesian Optimization with Noisy Experiments , 2017, Bayesian Analysis.
[8] Hao Huang,et al. STOCHASTIC OPTIMIZATION FOR FEASIBILITY DETERMINATION: AN APPLICATION TO WATER PUMP OPERATION IN WATER DISTRIBUTION NETWORK , 2018, 2018 Winter Simulation Conference (WSC).
[9] Douglas Allaire,et al. Multi-information source constrained Bayesian optimization , 2018, Structural and Multidisciplinary Optimization.
[10] P. Frazier. Bayesian Optimization , 2018, Hyperparameter Optimization in Machine Learning.
[11] Kirthevasan Kandasamy,et al. Multi-Fidelity Black-Box Optimization with Hierarchical Partitions , 2018, ICML.
[12] Régis Duvigneau,et al. A classification approach to efficient global optimization in presence of non-computable domains , 2018 .
[13] Hao Huang,et al. Multi-fidelity simulation optimization with level set approximation using probabilistic branch and bound , 2017, 2017 Winter Simulation Conference (WSC).
[14] Yaroslav D. Sergeyev,et al. Deterministic Global Optimization: An Introduction to the Diagonal Approach , 2017 .
[15] Kirthevasan Kandasamy,et al. Multi-fidelity Bayesian Optimisation with Continuous Approximations , 2017, ICML.
[16] Aaron Klein,et al. Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets , 2016, AISTATS.
[17] Matthias Poloczek,et al. Multi-Information Source Optimization , 2016, NIPS.
[18] Julien Bect,et al. A Bayesian approach to constrained single- and multi-objective optimization , 2015, Journal of Global Optimization.
[19] Yaroslav D. Sergeyev,et al. Deterministic Global Optimization , 2017 .
[20] Peter I. Frazier,et al. The Parallel Knowledge Gradient Method for Batch Bayesian Optimization , 2016, NIPS.
[21] Victor Picheny,et al. Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian , 2016, NIPS.
[22] G. Karniadakis,et al. Model inversion via multi-fidelity Bayesian optimization: a new paradigm for parameter estimation in haemodynamics, and beyond , 2016, Journal of The Royal Society Interface.
[23] Sébastien Le Digabel,et al. Modeling an Augmented Lagrangian for Blackbox Constrained Optimization , 2014, Technometrics.
[24] Alkis Gotovos,et al. Safe Exploration for Optimization with Gaussian Processes , 2015, ICML.
[25] Bernd Bischl,et al. Model-Based Multi-objective Optimization: Taxonomy, Multi-Point Proposal, Toolbox and Benchmark , 2015, EMO.
[26] Matthew W. Hoffman,et al. Predictive Entropy Search for Bayesian Optimization with Unknown Constraints , 2015, ICML.
[27] A. Basudhar,et al. Constrained efficient global optimization with support vector machines , 2012, Structural and Multidisciplinary Optimization.
[28] Robert B. Gramacy,et al. Optimization Under Unknown Constraints , 2010, 1004.4027.
[29] D. Ginsbourger,et al. Dealing with asynchronicity in parallel Gaussian Process based global optimization , 2010 .
[30] D. Ginsbourger,et al. A Multi-points Criterion for Deterministic Parallel Global Optimization based on Gaussian Processes , 2008 .
[31] M. Emmerich,et al. The computation of the expected improvement in dominated hypervolume of Pareto front approximations , 2008 .
[32] Yaroslav D. Sergeyev,et al. A one-dimensional local tuning algorithm for solving GO problems with partially defined constraints , 2007, Optim. Lett..
[33] Donald R. Jones,et al. Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..
[34] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[35] L. Rudenko. Objective functional approximation in a partially defined optimization problem , 1994 .