27 search results - page 1 / 6 » Dimension Reduction for Regression with Bottleneck Neural Ne... |
IDEAL
2010
Springer
13 years 2 months ago
2010
Springer
Dimension reduction for regression (DRR) deals with the problem of finding for high-dimensional data such low-dimensional representations, which preserve the ability to predict a ...
ICANN
2010
Springer
13 years 4 months ago
2010
Springer
Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...
ICANN
2003
Springer
13 years 9 months ago
2003
Springer
In independent component analysis problems, when we use a one-unit objective function to iteratively estimate several independent components, the uncorrelatedness between the indep...
IJCNN
2008
IEEE
13 years 10 months ago
2008
IEEE
Abstract— This paper presents a novel support vector regression (SVR) network for financial time series prediction. The SVR network consists of two layers of SVR: transformation...
SYRCODIS
2007
13 years 5 months ago
2007
High complexity of lattice construction algorithms and uneasy way of visualising lattices are two important problems connected with the formal concept analysis. Algorithm complexi...