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ICONIP
2007
15 years 2 months ago
Principal Component Analysis for Sparse High-Dimensional Data
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
Tapani Raiko, Alexander Ilin, Juha Karhunen
ESANN
2003
15 years 2 months ago
Neural networks organizations to learn complex robotic functions
Abstract. This paper considers the general problem of function estimation with a modular approach of neural computing. We propose to use functionally independent subnetworks to lea...
Gilles Hermann, Patrice Wira, Jean-Philippe Urban
CSDA
2007
128views more  CSDA 2007»
15 years 1 months ago
Regularized linear and kernel redundancy analysis
Redundancy analysis (RA) is a versatile technique used to predict multivariate criterion variables from multivariate predictor variables. The reduced-rank feature of RA captures r...
Yoshio Takane, Heungsun Hwang
JNW
2007
118views more  JNW 2007»
15 years 1 months ago
Alternate Routing in Tandem Traffic-Groomed Optical Networks
— Recent advances in telecommunication networks have allowed WDM to emerge as a viable solution to the ever-increasing demands of the Internet. Because these networks carry large...
Alicia Nicki Washington, Harry G. Perros
COMPUTING
2004
115views more  COMPUTING 2004»
15 years 1 months ago
Length Preserving Multiresolution Editing of Curves
In this paper a method for multiresolution deformation of planar piecewise linear curves that preserves the curve length is presented. In a wavelet based multiresolution editing f...
Basile Sauvage, Stefanie Hahmann, Georges-Pierre B...