ZOOpt: Toolbox for Derivative-Free Optimization

Parallel pareto optimization for subset selection

C. Qian, J. Shi, Y. Yu, K. Tang, and Z. Zhou · 1945

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Derivative-free optimization of high-dimensional non-convex functions by sequential random embeddings

H. Qian, Y.-Q. Hu, and Y. Yu · 1952

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Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES)

N. Hansen, S. D. Müller, and P. Koumoutsakos · 2003

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A tutorial on the cross-entropy method

P. de Boer, D. P. Kroese, S. Mannor, and R. Y. Rubinstein · 2005

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Trading convexity for scalability

R. Collobert, F. H. Sinz, J. Weston, and L. Bottou · 2006

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DEAP: Evolutionary algorithms made easy

F.-A. Fortin, F.-M. De Rainville, M.-A. Gardner, M. Parizeau, and C. Gagné · 2012

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Practical Bayesian optimization of machine learning algorithms

J. Snoek, H. Larochelle, and R. P. Adams · 2012

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Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures

J. Bergstra, D. Yamins, and D. D. Cox · 2013

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Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms

C. Thornton, F. Hutter, H. H. Hoos, and K. Leyton-Brown · 2013

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From bandits to Monte-Carlo Tree Search: The optimistic principle applied to optimization and planning

R. Munos · 2014

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Efficient and robust automated machine learning

M. Feurer, A. Klein, K. Eggensperger, J. T. Springenberg, M. Blum, and F. Hutter · 2015

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Subset selection by pareto optimization

C. Qian, Y. Yu, and Z.-H. Zhou · 2015

Cited alongside, same era.

Taking the human out of the loop: A review of Bayesian optimization

B. Shahriari, K. Swersky, Z. Wang, R. P. Adams, and N. de Freitas · 2016

Cited alongside, same era.

Bayesian optimization in a billion dimensions via random embeddings

Z. Wang, M. Zoghi, F. Hutter, D. Matheson, and N. D. Freitas · 2016

Subset selection under noise

C. Qian, J.-C. Shi, Y. Yu, K. Tang, and Z.-H. Zhou · 2017

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Large-scale evolution of image classifiers

E. Real, S. Moore, A. Selle, S. Saxena, Y. L. Suematsu, J. Tan, Q. V. Le, and A. Kurakin · 2017

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Evolution strategies as a scalable alternative to reinforcement learning

Original

T. Salimans, J. Ho, X. Chen, and I. Sutskever · 2017

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Ray: A distributed framework for emerging AI applications

P. Moritz, R. Nishihara, S. Wang, A. Tumanov, R. Liaw, E. Liang, M. Elibol, Z. Yang, W. Paul, M. I. Jordan, and I. Stoica · 2018

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Noisy derivative-free optimization with value suppression

H. Wang, H. Qian, and Y. Yu · 2018

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CMA-ES/pycma on Github

N. Hansen, Y. Akimoto, and P. Baudis · 2019

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