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ICANN
2010
Springer
13 years 7 months ago
Deep Bottleneck Classifiers in Supervised Dimension Reduction
Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...
Elina Parviainen
JMLR
2012
11 years 10 months ago
Deep Learning Made Easier by Linear Transformations in Perceptrons
We transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut connections to model th...
Tapani Raiko, Harri Valpola, Yann LeCun
ERSHOV
1999
Springer
13 years 12 months ago
Current Directions in Hyper-Programming
The traditional representation of a program is as a linear sequence of text. At some stage in the execution sequence the source text is checked for type correctness and its transla...
Ronald Morrison, Richard C. H. Connor, Quintin I. ...
NIPS
2000
13 years 9 months ago
Active Support Vector Machine Classification
An active set strategy is applied to the dual of a simple reformulation of the standard quadratic program of a linear support vector machine. This application generates a fast new...
Olvi L. Mangasarian, David R. Musicant
EUROGP
2005
Springer
156views Optimization» more  EUROGP 2005»
14 years 1 months ago
Evolving Rules for Document Classification
We describe a novel method for using Genetic Programming to create compact classification rules based on combinations of N-Grams (character strings). Genetic programs acquire fitne...
Laurence Hirsch, Masoud Saeedi, Robin Hirsch