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» Neural methods for non-standard data
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ANNPR
2006
Springer
15 years 5 months ago
Hierarchical Neural Networks Utilising Dempster-Shafer Evidence Theory
Abstract. Hierarchical neural networks show many benefits when employed for classification problems even when only simple methods analogous to decision trees are used to retrieve t...
Rebecca Fay, Friedhelm Schwenker, Christian Thiel,...
SSPR
1998
Springer
15 years 6 months ago
Modified Minimum Classification Error Learning and Its Application to Neural Networks
A novel method to improve the generalization performance of the Minimum Classification Error (MCE) / Generalized Probabilistic Descent (GPD) learning is proposed. The MCE/GPD learn...
Hiroshi Shimodaira, Jun Rokui, Mitsuru Nakai
GECCO
2006
Springer
178views Optimization» more  GECCO 2006»
15 years 5 months ago
A dynamic approach to artificial immune systems utilizing neural networks
The purpose of this work is to propose an immune-inspired setup to use a self-organizing map as a computational model for the interaction of antigens and antibodies. The proposed ...
Stefan Schadwinkel, Werner Dilger
NC
1998
102views Neural Networks» more  NC 1998»
15 years 3 months ago
Outliers and Bayesian Inference
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
Peter Sykacek
ICANN
2003
Springer
15 years 7 months ago
Optimizing Property Codes in Protein Data Reveals Structural Characteristics
We search for assignments of numbers to the amino acids (property codes) that maximize the autocorrelation function signal in given protein sequence data by an iterative method. Ou...
Olaf Weiss, Andreas Ziehe, Hanspeter Herzel