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ICML
2008
IEEE
15 years 10 months ago
Classification using discriminative restricted Boltzmann machines
Recently, many applications for Restricted Boltzmann Machines (RBMs) have been developed for a large variety of learning problems. However, RBMs are usually used as feature extrac...
Hugo Larochelle, Yoshua Bengio
TNN
2008
95views more  TNN 2008»
14 years 9 months ago
A Constrained Optimization Approach to Preserving Prior Knowledge During Incremental Training
In this paper, a supervised neural network training technique based on constrained optimization is developed for preserving prior knowledge of an input
Silvia Ferrari, Mark Jensenius
KSEM
2009
Springer
15 years 4 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer
IJON
2000
80views more  IJON 2000»
14 years 9 months ago
Synthesis approach for bidirectional associative memories based on the perceptron training algorithm
Bidirectional associative memories are being used extensively for solving a variety of problems related to pattern recognition. In the present paper, a new synthesis approach is d...
Ismail Salih, Stanley H. Smith, Derong Liu
TSMC
2002
119views more  TSMC 2002»
14 years 9 months ago
A cloning approach to classifier training
The Al-Alaoui algorithm is a weighted mean-square error (MSE) approach to pattern recognition. It employs cloning of the erroneously classified samples to increase the population o...
M. A. Al-Alaoui, R. Mouci, M. M. Mansour, Rony Fer...