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Distillation (Hinton et al., 2015) and privileged information (Vapnik & Izmailov, 2015) are two techniques that enable machines to learn from other machines.
Improving the accuracy and speed of support vector learning machines
Burges, Christopher and Schölkopf, Bernhard · 1997
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Statistical learning theory
Vapnik, Vladimir · 1998
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The SARCOS dataset, 2000
Vijayakumar, Sethu · 2000
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Model compression
Buciluǎ, Cristian, Caruana, Rich, and Niculescu-Mizil, Alexandru · 2006
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Inference with the Universum
Weston, Jason, Collobert, Ronan, Sinz, Fabian, Bottou, Léon, and Vapnik, Vladimir · 2006
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An analysis of inference with the Universum
Chapelle, Olivier, Agarwal, Alekh, Sinz, Fabian H, and Schölkopf, Bernhard · 2007
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Curriculum learning
Bengio, Yoshua, Louradour, Jérôme, Collobert, Ronan, and Weston, Jason · 2009
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The CIFAR-10 and CIFAR-100 datasets, 2009
Krizhevsky, Alex · 2009
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A new learning paradigm: Learning using privileged information
Vapnik, Vladimir and Vashist, Akshay · 2009
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On the theory of learning with privileged information
Pechyony, Dmitry and Vapnik, Vladimir · 2010
Cited alongside, same era.
Financial distress model prediction using SVM+
Ribeiro, Bernardete, Silva, Catarina, Vieira, Armando, Gaspar-Cunha, António, and das Neves, João C · 2010
Cited alongside, same era.
Privileged information for data clustering
Feyereisl, Jan and Aickelin, Uwe · 2012
Cited alongside, same era.
On causal and anticausal learning
Schölkopf, Bernhard, Janzing, Dominik, Peters, Jonas, Sgouritsa, Eleni, Zhang, Kun, and Mooij, Joris · 2012
Cited alongside, same era.
Incorporating privileged information through metric learning
Fouad, Shereen, Tino, Peter, Raychaudhury, Somak, and Schneider, Petra · 2013
Cited alongside, same era.
Efficient estimation of word representations in vector space
Mikolov, Tomas, Chen, Kai, Corrado, Greg, and Dean, Jeffrey · 2013
Cited alongside, same era.
From machine learning to machine reasoning
Bottou, Léon · 2014
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Mind the nuisance: Gaussian process classification using privileged noise
Hernández-Lobato, Daniel, Sharmanska, Viktoriia, Kersting, Kristian, Lampert, Christoph H, and Quadrianto, Novi · 2014
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Learning using privileged information: Svm+ and weighted svm
Lapin, Maksim, Hein, Matthias, and Schiele, Bernt · 2014
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Randomized nonlinear component analysis
Lopez-Paz, David, Sra, Suvrit, Smola, Alex, Ghahramani, Zoubin, and Schölkopf, Bernhard · 2014
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Learning and transferring mid-level image representations using convolutional neural networks
Oquab, Maxime, Bottou, Leon, Laptev, Ivan, and Sivic, Josef · 2014
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Learning to transfer privileged information
Sharmanska, Viktoriia, Quadrianto, Novi, and Lampert, Christoph H · 2014
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Learning to rank using privileged information
Sharmanska, Viktoriia, Quadrianto, Novi, and Lampert, Christoph H · 2013
Cited alongside, same era.
Do deep nets really need to be deep?
Ba, Jimmy and Caruana, Rich · 2014
Cited alongside, same era.
Gradient-based learning applied to document recognition
LeCun, Yann, Bottou, Léon, Bengio, Yoshua, and Haffner, Patrick
Cited in the paper.
The MNIST database of handwritten digits, 1998b
LeCun, Yann, Cortes, Corinna, and Burges, Christopher JC
Cited in the paper.
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Distilling the knowledge in a neural network
Hinton, Geoffrey, Vinyals, Oriol, and Dean, Jeff · 2015
Closest in time.
Learning using privileged information: Similarity control and knowledge transfer
Vapnik, Vladimir and Izmailov, Rauf · 2015
Closest in time.