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NN
2002
Springer
125views Neural Networks» more  NN 2002»
13 years 7 months ago
Generalized relevance learning vector quantization
We propose a new scheme for enlarging generalized learning vector quantization (GLVQ) with weighting factors for the input dimensions. The factors allow an appropriate scaling of ...
Barbara Hammer, Thomas Villmann
IJON
2000
71views more  IJON 2000»
13 years 7 months ago
Variable selection using neural-network models
In this paper we propose an approach to variable selection that uses a neural-network model as the tool to determine which variables are to be discarded. The method performs a bac...
Giovanna Castellano, Anna Maria Fanelli
AR
2011
13 years 2 months ago
Real-Time Pose-Invariant Face Recognition Using the Efficient Second-Order Minimization and the Pose Transforming Matrix
We propose a real-time pose invariant face recognition algorithm from a gallery of frontal images only. First, we modified the second order minimization method for active appearan...
Hyun-Chul Choi, Se-Young Oh
BMCBI
2006
112views more  BMCBI 2006»
13 years 8 months ago
Distill: a suite of web servers for the prediction of one-, two- and three-dimensional structural features of proteins
Background: We describe Distill, a suite of servers for the prediction of protein structural features: secondary structure; relative solvent accessibility; contact density; backbo...
Davide Baù, Alberto J. M. Martin, Catherine...
ICANN
2010
Springer
13 years 9 months ago
Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines
Abstract. Learning algorithms relying on Gibbs sampling based stochastic approximations of the log-likelihood gradient have become a common way to train Restricted Boltzmann Machin...
Asja Fischer, Christian Igel