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Bayesian optimization (BO) is a sample-efficient approach for tuning design parameters to optimize expensive-to-evaluate, black-box performance metrics.
On the likelihood that one unknown probability exceeds another in view of the evidence of two samples
William R. Thompson · 1933
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G. Taguchi · 1989
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Robust Optimal Design for Worst-Case Tolerances
G. Emch and A. Parkinson · 1994
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A limited memory algorithm for bound constrained optimization
Richard H. Byrd, Peihuang Lu, Jorge Nocedal, and Ciyou Zhu · 1995
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Algorithm 778: L-bfgs-b: Fortran subroutines for large-scale bound-constrained optimization
Ciyou Zhu, Richard H. Byrd, Peihuang Lu, and Jorge Nocedal · 1997
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Nonlinear Multiobjective Optimization , volume 12 of International Series in Operations Research & Management Science
Miettinen Kaisa · 1999
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Multi-objective optimization in material design and selection
M.F. Ashby · 2000
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A fast and elitist multiobjective genetic algorithm: Nsga-ii
K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan · 2002
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A swarm metaphor for multiobjective design optimization
Tapabrata Ray and K.M. Liew · 2002
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Conditional value-at-risk for general loss distributions
R.Tyrrell Rockafellar and Stanislav Uryasev · 2002
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Robust design of structures using optimization methods
Ioannis Doltsinis and Zhan Kang · 2003
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Quasi-monte carlo sampling
Art B Owen · 2003
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Nonstationary Gaussian Processes for Regression and Spatial Modelling
C.J. Paciorek · 2003
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Gaussian Processes in Machine Learning , pages 63–71
Carl Edward Rasmussen · 2004
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Searching for robust pareto-optimal solutions in multi-objective optimization
Kalyanmoy Deb and Himanshu Gupta · 2005
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Handling constraints in robust multi-objective optimization
Himanshu Gupta and Kalyanmoy Deb · 2005
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Single- and multiobjective evolutionary optimization assisted by gaussian random field metamodels
M. T. M. Emmerich, K. C. Giannakoglou, and B. Naujoks · 2006
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Parego: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems
J. Knowles · 2006
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Robust optimization – a comprehensive survey
Hans-Georg Beyer and Bernhard Sendhoff · 2007
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Multi-task gaussian process prediction
Edwin V Bonilla, Kian Chai, and Christopher Williams · 2007
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The CMA Evolution Strategy: A Comparing Review , volume 192, pages 75–102
Nikolaus Hansen · 2007
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Embedded evolutionary multi-objective optimization for worst case robustness
Gideon Avigad and Jürgen Branke · 2008
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Multiobjective optimization for crash safety design of vehicles using stepwise regression model
Xingtao Liao, Qing Li, Xujing Yang, Weigang Zhang, and Wei Li · 2008
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Random features for large-scale kernel machines
Ali Rahimi and Benjamin Recht · 2008
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Value- at-risk vs conditional value-at-risk in risk management and optimization
Sergey Sarykalin, Gaia Serraino, and Stan Uryasev · 2008
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Approximation Theorems of Mathematical Statistics
Robert J. Serfling · 2008
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Estimating quantile sensitivities
L. Jeff Hong · 2009
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Bayesian gaussian processes for sequential prediction, optimisation and quadrature
Michael A. Osborne · 2010
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Gaussian process optimization in the bandit setting: No regret and experimental design
Niranjan Srinivas, Andreas Krause, Sham Kakade, and Matthias Seeger · 2010
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A many-objective test problem for visually examining diversity maintenance behavior in a decision space
Hisao Ishibuchi, Naoya Akedo, and Yusuke Nojima · 2011
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Fundamental review of the trading book
Basel Committee on Banking Supervision · 2012
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Exponential regret bounds for gaussian process bandits with deterministic observations
Nando de Freitas, Alex Smola, and Masrour Zoghi · 2012
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Multivariate value at risk and related topics
Andràs Prèkopa · 2012
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Batched large-scale bayesian optimization in high-dimensional spaces, 2018
Zi Wang, Clement Gehring, Pushmeet Kohli, and Stefanie Jegelka · 2018
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Maximizing acquisition functions for bayesian optimization
James Wilson, Frank Hutter, and Marc Deisenroth · 2018
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A multi-objective robust optimization approach based on gaussian process model
Qi Zhou, Ping Jiang, Xiang Huang, Feng Zhang, and Taotao Zhou · 2018
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Bayesian optimization of composite functions
Raul Astudillo and Peter Frazier · 2019
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Gaussian process optimization with adaptive sketching: Scalable and no regret, 2019
Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, and Lorenzo Rosasco · 2019
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Constrained bayesian optimization with noisy experiments
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Diederik P Kingma and Max Welling · 2013
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Worst-case global optimization of black-box functions through kriging and relaxation
Julien Marzat, Eric Walter, and Hélène Piet-Lahanier · 2013
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Pareto front modeling for sensitivity analysis in multi-objective bayesian optimization
Roberto Calandra and Jan Peters · 2014
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On multivariate extensions of conditional-tail-expectation
Areski Cousin and Elena Di Bernardino · 2014
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Monte carlo methods for value-at-risk and conditional value-at-risk: a review
L Jeff Hong, Zhaolin Hu, and Guangwu Liu · 2014
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Concepts of efficiency for uncertain multi-objective optimization problems based on set order relations
Jonas Ide and Elisabeth Köbis · 2014
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Efficient kriging-based robust optimization of unconstrained problems
Samee ur Rehman, Matthijs Langelaar, and Fred van Keulen · 2014
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Benjamin Letham, Brian Karrer, Guilherme Ottoni, and Eytan Bakshy · 2019
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Bayesian optimisation under uncertain inputs
Rafael Oliveira, Lionel Ott, and Fabio Ramos · 2019
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Robust process design in pharmaceutical manufacturing under batch-to-batch variation
Xiangzhong Xie and René Schenkendorf · 2019
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Multi-objective bayesian global optimization using expected hypervolume improvement gradient
Kaifeng Yang, Michael Emmerich, André Deutz, and Thomas Bäck · 2019
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BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization
Maximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, and Eytan Bakshy · 2020
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pymoo: Multi-objective optimization in python
J. Blank and K. Deb · 2020
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Bayesian optimization of risk measures
Sait Cakmak, Raul Astudillo, Peter Frazier, and Enlu Zhou · 2020
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Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization
Samuel Daulton, Maximilian Balandat, and Eytan Bakshy · 2020
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Noisy-input entropy search for efficient robust bayesian optimization
Lukas Fröhlich, Edgar Klenske, Julia Vinogradska, Christian Daniel, and Melanie Zeilinger · 2020
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Distributionally robust bayesian optimization
Johannes Kirschner, Ilija Bogunovic, Stefanie Jegelka, and Andreas Krause · 2020
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Diversity-Guided Multi-Objective Bayesian Optimization With Batch Evaluations
Mina Konakovic Lukovic, Yunsheng Tian, and Wojciech Matusik · 2020
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Mixed strategies for robust optimization of unknown objectives, 2020
Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, and Andreas Krause · 2020
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Multi-objective bayesian optimization using pareto-frontier entropy, 2020
Shinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, and Masayuki Karasuyama · 2020
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An easy-to-use real-world multi-objective optimization problem suite
Ryoji Tanabe and Hisao Ishibuchi · 2020
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Bayesian quantile and expectile optimisation
Léonard Torossian, Victor Picheny, and Nicolas Durrande · 2020
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Efficiently sampling functions from gaussian process posteriors
James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, and Marc Peter Deisenroth · 2020
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Bayesian optimization for robust design of steel frames with joint and individual probabilistic constraints
Bach Do, Makoto Ohsaki, and Makoto Yamakawa · 2021
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Latency-aware neural architecture search with multi-objective bayesian optimization, 2021
David Eriksson, Pierce I-Jen Chuang, Samuel Daulton, Peng Xia, Akshat Shrivastava, Arun Babu, Shicong Zhao, Ahmed Aly, Ganesh Venkatesh, and Maximilian Balandat · 2021
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Mean-variance analysis in bayesian optimization under uncertainty
Shogo Iwazaki, Yu Inatsu, and Ichiro Takeuchi · 2021
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Bag of baselines for multi-objective joint neural architecture search and hyperparameter optimization
Sergio Izquierdo, Julia Guerrero-Viu, Sven Hauns, Guilherme Miotto, Simon Schrodi, André Biedenkapp, Thomas Elsken, Difan Deng, Marius Lindauer, and Frank Hutter · 2021
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Scalable bayesian optimization accelerates process optimization of penicillin production
Qiaohao Liang and Lipeng Lai · 2021
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Beyond the pareto efficient frontier: Constraint active search for multiobjective experimental design
Gustavo Malkomes, Bolong Cheng, Eric H Lee, and Mike Mccourt · 2021
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