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In practical Bayesian optimization, we must often search over structures with differing numbers of parameters.
Gradient-based learning applied to document recognition
Yann Lecun, Lon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Gaussian Processes for Machine Learning
Carl E. Rasmussen and Christopher K.I. Williams · 2006
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A fast learning algorithm for deep belief nets
Geoffrey E. Hinton, Simon Osindero, and Yee-Whye Teh · 2006
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Automated Configuration of Algorithms for Solving Hard Computational Problems
Frank Hutter · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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A Bayesian interactive optimization approach to procedural animation design
Eric Brochu, Tyson Brochu, and Nando de Freitas · 2010
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Recurrent neural network based language model
Tomas Mikolov, Martin Karafiát, Lukas Burget, Jan Cernockỳ, and Sanjeev Khudanpur · 2010
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Slice sampling covariance hyperparameters of latent Gaussian models
Iain Murray and Ryan P. Adams · 2010
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Dynamic trees for learning and design
Matthew A. Taddy, Robert B. Gramacy, and Nicholas G. Polson · 2011
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Sequential model-based optimization for general algorithm configuration
Frank Hutter, Holger H. Hoos, and Kevin Leyton-Brown · 2011
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Algorithms for hyper-parameter optimization
James Bergstra, Rémi Bardenet, Yoshua Bengio, Balázs Kégl, et al · 2011
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An analysis of single-layer networks in unsupervised feature learning
Adam Coates, Honglak Lee, and Andrew Y Ng · 2011
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Practical Bayesian optimization of machine learning algorithms
Jasper Snoek, Hugo Larochelle, and Ryan Prescott Adams · 2012
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Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups
Geoffrey E. Hinton, Li Deng, Dong Yu, George E. Dahl, Abdel rahman Mohamed, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke, Patrick Nguyen, Tara N. Sainath, and Brian Kingsbury · 2012
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Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2012
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Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures
James Bergstra, Daniel Yamins, and David Cox · 2013
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Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms
Chris Thornton, Frank Hutter, Holger H. Hoos, and Kevin Leyton-Brown · 2013
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoff Hinton · 2012
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Frank Hutter and Michael A. Osborne · 2013
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Regularization of neural networks using dropconnect
Li Wan, Matthew Zeiler, Sixin Zhang, Yann L Cun, and Rob Fergus · 2013
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