374 search results - page 47 / 75 » Training the random neural network using quasi-Newton method... |
ICANN
2009
Springer
15 years 6 months ago
2009
Springer
The best recent supervised sequence learning methods use gradient descent to train networks of miniature nets called memory cells. The most popular cell structure seems somewhat ar...
COLT
1995
Springer
15 years 3 months ago
1995
Springer
The Noise Sensitivity Signature (NSS), originally introduced by Grossman and Lapedes (1993), was proposed as an alternative to cross validation for selecting network complexity. I...
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JMLR
2012
13 years 2 months ago
2012
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
ASUNAM
2010
IEEE
15 years 1 months ago
2010
IEEE
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
ICANN
2010
Springer
14 years 12 months ago
2010
Springer
Independent Component Analysis (ICA) is a statistical computation method that transforms a random vector in another one whose components are independent. Because the marginal distr...