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Machine learning models are often tuned by nesting optimization of model weights inside the optimization of hyperparameters.
Approximation capabilities of multilayer feedforward networks
Hornik, Kurt · 1991
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The theory of learning in games , volume 2
Fudenberg, Drew and Levine, David K · 1998
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Gradient-based learning applied to document recognition
LeCun, Yann, Bottou, Léon, Bengio, Yoshua, and Haffner, Patrick · 1998
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Gaussian processes for machine learning , volume 1
Rasmussen, Carl Edward and Williams, Christopher KI · 2006
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Practical bayesian optimization
Lizotte, Daniel James · 2008
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Rectified linear units improve restricted boltzmann machines
Nair, Vinod and Hinton, Geoffrey E · 2010
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Stackelberg games for adversarial prediction problems
Brückner, Michael and Scheffer, Tobias · 2011
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Random search for hyper-parameter optimization
Bergstra, James and Bengio, Yoshua · 2012
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Generic methods for optimization-based modeling
Domke, Justin · 2012
Cited alongside, same era.
Practical bayesian optimization of machine learning algorithms
Snoek, Jasper, Larochelle, Hugo, and Adams, Ryan P · 2012
Cited alongside, same era.
Generative adversarial nets
Goodfellow, Ian, Pouget-Abadie, Jean, Mirza, Mehdi, Xu, Bing, Warde-Farley, David, Ozair, Sherjil, Courville, Aaron, and Bengio, Yoshua · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
Kingma, Diederik and Ba, Jimmy · 2014
Cited alongside, same era.
Freeze-thaw bayesian optimization
Swersky, Kevin, Snoek, Jasper, and Adams, Ryan Prescott · 2014
Cited alongside, same era.
Ha, David, Dai, Andrew, and Le, Quoc V · 2016
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Hyperband: A novel bandit-based approach to hyperparameter optimization
Li, Lisha, Jamieson, Kevin, DeSalvo, Giulia, Rostamizadeh, Afshin, and Talwalkar, Ameet · 2016
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Scalable gradient-based tuning of continuous regularization hyperparameters
Luketina, Jelena, Berglund, Mathias, Greff, Klaus, and Raiko, Tapani · 2016
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Hyperparameter optimization with approximate gradient
Pedregosa, Fabian · 2016
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Smash: One-shot model architecture search through hypernetworks
Brock, Andrew, Lim, Theodore, Ritchie, JM, and Weston, Nick · 2017
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Blundell, Charles, Cornebise, Julien, Kavukcuoglu, Koray, and Wierstra, Daan · 2015
Cited alongside, same era.
Autograd: Effortless gradients in numpy
Maclaurin, Dougal, Duvenaud, David, and Adams, Ryan P · 2015
Cited alongside, same era.
Fu, Jie, Luo, Hongyin, Feng, Jiashi, Low, Kian Hsiang, and Chua, Tat-Seng · 2016
Cited alongside, same era.
Gradient-based hyperparameter optimization through reversible learning
Maclaurin, Dougal, Duvenaud, David, and Adams, Ryan
Cited in the paper.
Gradient-based regularization parameter selection for problems with non-smooth penalty functions
Feng, Jean and Simon, Noah · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks
Finn, Chelsea, Abbeel, Pieter, and Levine, Sergey · 2017
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Forward and reverse gradient-based hyperparameter optimization
Franceschi, Luca, Donini, Michele, Frasconi, Paolo, and Pontil, Massimiliano · 2017
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