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We introduce Deep Linear Discriminant Analysis (DeepLDA) which learns linearly separable latent representations in an end-to-end fashion.
The use of multiple measurements in taxonomic problems
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Regularized discriminant analysis
Friedman, Jerome H · 1989
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The elements of statistical learning , volume 1
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Regularization studies of linear discriminant analysis in small sample size scenarios with application to face recognition
Lu, Juwei, Plataniotis, Konstantinos N, and Venetsanopoulos, Anastasios N · 2005
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An analysis of single-layer networks in unsupervised feature learning
Coates, Adam, Ng, Andrew Y, and Lee, Honglak · 2011
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Swersky, Kevin, Snoek, Jasper, and Adams, Ryan P · 2013
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On deep multi-view representation learning
Wang, Weiran, Arora, Raman, Livescu, Karen, and Bilmes, Jeff
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Unsupervised learning of acoustic features via deep canonical correlation analysis
Wang, Weiran, Arora, Raman, Livescu, Karen, and Bilmes, Jeff A
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
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