Sciweavers

ESANN
2008
13 years 6 months ago
Phase transitions in Vector Quantization
Abstract. We study Winner-Takes-All and rank based Vector Quantization along the lines of the statistical physics of off-line learning. Typical behavior of the system is obtained w...
Aree Witoelar, Anarta Ghosh, Michael Biehl
IBPRIA
2003
Springer
13 years 10 months ago
Reducing Training Sets by NCN-based Exploratory Procedures
In this paper, a new approach to training set size reduction is presented. This scheme basically consists of defining a small number of prototypes that represent all the original ...
María Teresa Lozano, José Salvador S...
CAEPIA
2003
Springer
13 years 10 months ago
Using the Geometrical Distribution of Prototypes for Training Set Condensing
Abstract. In this paper, some new approaches to training set size reduction are presented. These schemes basically consist of defining a small number of prototypes that represent ...
María Teresa Lozano, José Salvador S...
IJCNN
2006
IEEE
13 years 11 months ago
Particle Swarm Optimization of Fuzzy ARTMAP Parameters
— In this paper a Particle Swarm Optimization (PSO)-based training strategy is introduced for fuzzy ARTMAP that minimizes generalization error while optimizing parameter values. ...
Eric Granger, Philippe Henniges, Luiz S. Oliveira,...
ICML
2000
IEEE
14 years 5 months ago
Less is More: Active Learning with Support Vector Machines
We describe a simple active learning heuristic which greatly enhances the generalization behavior of support vector machines (SVMs) on several practical document classification ta...
Greg Schohn, David Cohn
ICPR
2004
IEEE
14 years 6 months ago
A Pattern Synthesis Technique with an Efficient Nearest Neighbor Classifier for Binary Pattern Recognition
Important factors affecting the efficiency and performance of the nearest neighbor classifier (NNC) are space, classification time requirements and for high dimensional data, due ...
M. Narasimha Murty, P. Viswanath, Shalabh Bhatnaga...
ICPR
2004
IEEE
14 years 6 months ago
The Characterization of Classification Problems by Classifier Disagreements
In this paper we try to characterize a set of classification problems. For this, we use the disagreement between a set of standard classifiers. The disagreement patterns do not on...
David M. J. Tax, Elzbieta Pekalska, Robert P. W. D...