PR
2007
13 years 12 months ago
2007
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...
ISCI
1998
14 years 3 days ago
1998
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...
JMLR
2006
14 years 12 days ago
2006
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....
ISCI
2006
14 years 12 days ago
2006
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...
CORR
2006
Springer
14 years 14 days ago
2006
Springer
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...
IJCAI
1989
14 years 1 months ago
1989
Multilayered feedforward neural networks possess a number of properties which make them particularly suited to complex pattern classification problems. However, their application ...
NIPS
1994
14 years 1 months ago
1994
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...
ICGA
1993
14 years 1 months ago
1993
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...
IWFM
2000
14 years 1 months ago
2000
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...
ESANN
2003
14 years 1 months ago
2003
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...