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Optimizing multiple competing black-box objectives is a challenging problem in many fields, including science, engineering, and machine learning.
Efficient computation of expected hypervolume improvement using box decomposition algorithms
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On the likelihood that one unknown probability exceeds another in view of the evidence of two samples
Thompson, W. R · 1933
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An analysis of approximations for maximizing submodular set functions—II , pp. 73–87
Fisher, M. L., Nemhauser, G. L., and Wolsey, L. A · 1978
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Efficient global optimization of expensive black-box functions
Jones, D. R., Schonlau, M., and Welch, W. J · 1998
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A fast and elitist multiobjective genetic algorithm: Nsga-ii
Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T · 2002
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Scalable multi-objective optimization test problems
Deb, K., Thiele, L., Laumanns, M., and Zitzler, E · 2002
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Gaussian Processes in Machine Learning , pp. 63–71
Rasmussen, C. E · 2004
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Reliability-based design optimization for crashworthiness of vehicle side impact
Youn, B. D., Choi, K., Yang, R.-J., and Gu, L · 2004
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Single- and multiobjective evolutionary optimization assisted by gaussian random field metamodels
Emmerich, M. T. M., Giannakoglou, K. C., and Naujoks, B · 2006
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Parego: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems
Knowles, J · 2006
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Covariance matrix adaptation for multi-objective optimization
Igel, C., Hansen, N., and Roth, S · 2007
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Random features for large-scale kernel machines
Rahimi, A. and Recht, B · 2007
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Stochastic submodular maximization
Asadpour, A., Nazerzadeh, H., and Saberi, A · 2008
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Reliability-based optimization using evolutionary algorithms
Deb, K., Gupta, S., Daum, D., Branke, J., Mall, A. K., and Padmanabhan, D · 2009
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Using highly efficient nonlinear experimental design methods for optimization of lactococcus lactis fermentation in chemically defined media
Zhang, G. and Block, D. E · 2009
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Expensive multiobjective optimization by moea/d with gaussian process model
Zhang, Q., Liu, W., Tsang, E., and Virginas, B · 2009
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Mnist handwritten digit database
LeCun, Y., Cortes, C., and Burges, C · 2010
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Bayesian gaussian processes for sequential prediction, optimisation and quadrature
Osborne, M. A · 2010
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Speech recognition for mobile devices at google
Schuster, M · 2010
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Towards efficient multiobjective optimization: Multiobjective statistical criterions
Couckuyt, I., Deschrijver, D., and Dhaene, T · 2012
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A multiobjective evolutionary algorithm based on decomposition and probability model
Zhou, A., Zhang, Q., and Zhang, G · 2012
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Auto-Encoding Variational Bayes
Kingma, D. P. and Welling, M · 2013
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Pareto front modeling for sensitivity analysis in multi-objective bayesian optimization
Calandra, R. and Peters, J · 2014
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Bayesian optimization with unknown constraints
Gelbart, M. A., Snoek, J., and Adams, R. P · 2014
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Predictive entropy search for efficient global optimization of black-box functions
Hernández-Lobato, J. M., Hoffman, M. W., and Ghahramani, Z · 2014
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Quantifying uncertainty on pareto fronts with gaussian process conditional simulations
Binois, M., Ginsbourger, D., and Roustant, O · 2015
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Predictive entropy search for multi-objective bayesian optimization, 2015
Using well-understood single-objective functions in multiobjective black-box optimization test suites, 2019
Brockhoff, D., Tusar, T., Auger, A., and Hansen, N · 2019
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Thompson sampling for contextual bandit problems with auxiliary safety constraints
Daulton, S., Singh, S., Avadhanula, V., Dimmery, D., and Bakshy, E · 2019
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Predictive entropy search for multi-objective bayesian optimization with constraints
Garrido-Merchán, E. C. and Hernández-Lobato, D · 2019
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Bayesian optimization for policy search via online-offline experimentation
Letham, B. and Bakshy, E · 2019
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Constrained bayesian optimization with noisy experiments
Letham, B., Karrer, B., Ottoni, G., and Bakshy, E · 2019
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Data-efficient learning of morphology and controller for a microrobot
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Hernández-Lobato, D., Hernández-Lobato, J. M., Shah, A., and Adams, R. P · 2015
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On the representation of the search region in multi-objective optimization
Klamroth, K., Lacour, R., and Vanderpooten, D · 2015
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Efficient multi-criteria optimization on noisy machine learning problems
Koch, P., Wagner, T., Emmerich, M. T., Back, T., and Konen, W · 2015
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Bayesian optimization for learning gaits under uncertainty
Calandra, R., Seyfarth, A., Peters, J., and Deisenroth, M. P · 2016
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Taking the human out of the loop: A review of bayesian optimization
Shahriari, B., Swersky, K., Wang, Z., Adams, R. P., and de Freitas, N · 2016
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Efficient computation of the search region in multi-objective optimization
Dächert, K., Klamroth, K., Lacour, R., and Vanderpooten, D · 2017
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First investigations on noisy model-based multi-objective optimization
Horn, D., Dagge, M., Sun, X., and Bischl, B · 2017
Cited alongside, same era.
Liao, T., Wang, G., Yang, B., Lee, R., Pister, K., Levine, S., and Calandra, R · 2019
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The evolution of high-throughput experimentation in pharmaceutical development and perspectives on the future
Mennen, S. M., Alhambra, C., Allen, C. L., Barberis, M., Berritt, S., Brandt, T. A., Campbell, A. D., Castañón, J., Cherney, A. H., Christensen, M., Damon, D. B., Eugenio de Diego, J., García-Cerrada, S., García-Losada, P., Haro, R., Janey, J., Leitch, D. C., Li, L., Liu, F., Lobben, P. C., MacMillan, D. W. C., Magano, J., McInturff, E., Monfette, S., Post, R. J., Schultz, D., Sitter, B. J., Stevens, J. M., Strambeanu, I. I., Twilton, J., Wang, K., and Zajac, M. A · 2019
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Regularized evolution for image classifier architecture search
Real, E., Aggarwal, A., Huang, Y., and Le, Q. V · 2019
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Uncrowded hypervolume improvement: Como-cma-es and the sofomore framework
Touré, C., Hansen, N., Auger, A., and Brockhoff, D · 2019
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BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization
Balandat, M., Karrer, B., Jiang, D. R., Daulton, S., Letham, B., Wilson, A. G., and Bakshy, E · 2020
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Differentiable expected hypervolume improvement for parallel multi-objective Bayesian optimization
Daulton, S., Balandat, M., and Bakshy, E · 2020
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High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization
Feng, Q., Letham, B., Bakshy, E., and Mao, H · 2020
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Parallel predictive entropy search for multi-objective bayesian optimization with constraints, 2020
Garrido-Merchán, E. C. and Hernández-Lobato, D · 2020
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Random hypervolume scalarizations for provable multi-objective black box optimization, 2020
Golovin, D. and Zhang, Q · 2020
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Multi-objective optimization of smallholder apple production: Lessons from the bohai bay region
Jiang, S., Zhang, H., Cong, W., Liang, Z., Ren, Q., Wang, C., Zhang, F., and Jiao, X · 2020
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Diversity-guided multi-objective bayesian optimization with batch evaluations
Lukovic, K. M., Tian, Y., and Matusik, W · 2020
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Distilled thompson sampling: Practical and efficient thompson sampling via imitation learning
Namkoong, H., Daulton, S., and Bakshy, E · 2020
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Multi-objective Bayesian optimization using pareto-frontier entropy
Suzuki, S., Takeno, S., Tamura, T., Shitara, K., and Karasuyama, M · 2020
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Multi-fidelity Bayesian optimization with max-value entropy search and its parallelization
Takeno, S., Fukuoka, H., Tsukada, Y., Koyama, T., Shiga, M., Takeuchi, I., and Karasuyama, M · 2020
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An easy-to-use real-world multi-objective optimization problem suite
Tanabe, R. and Ishibuchi, H · 2020
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