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Hyperparameters of deep neural networks are often optimized by grid search, random search or Bayesian optimization.
Completely derandomized self-adaptation in evolution strategies
Hansen, Nikolaus and Ostermeier, Andreas · 2001
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Gaussian Processes for Machine Learning
Rasmussen, C. and Williams, C · 2006
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A method for handling uncertainty in evolutionary optimization with an application to feedback control of combustion
Hansen, Nikolaus, Niederberger, André SP, Guzzella, Lino, and Koumoutsakos, Petros · 2009
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Kernel density estimation via diffusion
Botev, Zdravko I, Grotowski, Joseph F, Kroese, Dirk P, et al · 2010
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Algorithms for hyper-parameter optimization
Bergstra, J., Bardenet, R., Bengio, Y., and Kégl, B · 2011
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Sequential model-based optimization for general algorithm configuration
Hutter, F., Hoos, H., and Leyton-Brown, K · 2011
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Random search for hyper-parameter optimization
Bergstra, J. and Bengio, Y · 2012
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Parallel algorithm configuration
Hutter, F., Hoos, H., and Leyton-Brown, K · 2012
Cited alongside, same era.
Self-adaptive Surrogate-Assisted Covariance Matrix Adaptation Evolution Strategy
Loshchilov, Ilya, Schoenauer, Marc, and Sebag, Michele · 2012
Cited alongside, same era.
Adadelta: An adaptive learning rate method
Zeiler, Matthew D · 2012
Cited alongside, same era.
Fast computation of the multi-points expected improvement with applications in batch selection
Chevalier, Clément and Ginsbourger, David · 2013
Cited alongside, same era.
Towards an empirical foundation for assessing Bayesian optimization of hyperparameters
Eggensperger, K., Feurer, M., Hutter, F., Bergstra, J., Snoek, J., Hoos, H., and Leyton-Brown, K · 2013
Cited alongside, same era.
Bayesian optimization with unknown constraints
Gelbart, Michael A, Snoek, Jasper, and Adams, Ryan P · 2014
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Predictive entropy search for efficient global optimization of black-box functions
Hernández-Lobato, José Miguel, Hoffman, Matthew W, and Ghahramani, Zoubin · 2014
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Adam: A method for stochastic optimization
Kingma, Diederik and Ba, Jimmy · 2014
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Black box optimization for automatic speech recognition
Watanabe, Shigetaka and Le Roux, Jonathan · 2014
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Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves
Domhan, Tobias, Springenberg, Jost Tobias, and Hutter, Frank · 2015
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Loshchilov, Ilya, Schoenauer, Marc, and Sebag, Michèle · 2013
Cited alongside, same era.
Parallelizing exploration-exploitation tradeoffs in gaussian process bandit optimization
Desautels, Thomas, Krause, Andreas, and Burdick, Joel W · 2014
Cited alongside, same era.
Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures
Bergstra, J., Yamins, D., and Cox, D
Cited in the paper.
Practical Bayesian optimization of machine learning algorithms
Snoek, J., Larochelle, H., and Adams, R. P
Cited in the paper.
Practical bayesian optimization of machine learning algorithms
Snoek, Jasper, Larochelle, Hugo, and Adams, Ryan P
Cited in the paper.
Online batch selection for faster training of neural networks
Loshchilov, Ilya and Hutter, Frank · 2015
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Scalable bayesian optimization using deep neural networks
Snoek, Jasper, Rippel, Oren, Swersky, Kevin, Kiros, Ryan, Satish, Nadathur, Sundaram, Narayanan, Patwary, Md, Ali, Mostofa, Adams, Ryan P, et al · 2015
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