Sciweavers

Share
warning: Creating default object from empty value in /var/www/modules/taxonomy/taxonomy.module on line 1416.
PR
2007
118views more  PR 2007»
10 years 2 months ago
Shape recognition using eigenvalues of the Dirichlet Laplacian
The eigenvalues of the Dirichlet Laplacian are used to generate three different sets of features for shape recognition and classification in binary images. The generated feature...
Mohamed A. Khabou, Lotfi Hermi, Mohamed Ben Hadj R...
ISCI
1998
83views more  ISCI 1998»
10 years 2 months ago
On Generalization by Neural Networks
We report new results on the corner classification approach to training feedforward neural networks. It is shown that a prescriptive learning procedure where the weights are simp...
Subhash C. Kak
JMLR
2006
389views more  JMLR 2006»
10 years 2 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...
ISCI
2006
96views more  ISCI 2006»
10 years 2 months ago
A comparison of classification accuracy of four genetic programming-evolved intelligent structures
We investigate the effectiveness of GP-generated intelligent structures in classification tasks. Specifically, we present and use four context-free grammars to describe (1) decisi...
Athanasios Tsakonas
CORR
2006
Springer
135views Education» more  CORR 2006»
10 years 2 months ago
Classification of Ordinal Data
Many real life problems require the classification of items into naturally ordered classes. These problems are traditionally handled by conventional methods intended for the class...
Jaime S. Cardoso
IJCAI
1989
10 years 4 months ago
Training Feedforward Neural Networks Using Genetic Algorithms
Multilayered feedforward neural networks possess a number of properties which make them particularly suited to complex pattern classification problems. However, their application ...
David J. Montana, Lawrence Davis
NIPS
1994
10 years 4 months ago
Active Learning with Statistical Models
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...
ICGA
1993
145views Optimization» more  ICGA 1993»
10 years 4 months ago
Genetic Programming of Minimal Neural Nets Using Occam's Razor
A genetic programming method is investigated for optimizing both the architecture and the connection weights of multilayer feedforward neural networks. The genotype of each networ...
Byoung-Tak Zhang, Heinz Mühlenbein
IWFM
2000
112views Formal Methods» more  IWFM 2000»
10 years 4 months ago
A Note on the Relationships Between Logic Programs and Neural Networks
Several recent publications have exhibited relationships between the theories of logic programming and of neural networks. We consider a general approach to representing normal lo...
Pascal Hitzler, Anthony Karel Seda
ESANN
2003
10 years 4 months ago
Accelerating the convergence speed of neural networks learning methods using least squares
In this work a hybrid training scheme for the supervised learning of feedforward neural networks is presented. In the proposed method, the weights of the last layer are obtained em...
Oscar Fontenla-Romero, Deniz Erdogmus, José...
books