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» On Generalization by Neural Networks
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ISNN
2010
Springer
14 years 10 months ago
Extension of the Generalization Complexity Measure to Real Valued Input Data Sets
Abstract. This paper studies the extension of the Generalization Complexity (GC) measure to real valued input problems. The GC measure, defined in Boolean space, was proposed as a...
Iván Gómez, Leonardo Franco, Jos&eac...
IJCAI
2001
15 years 1 months ago
Genetic Algorithm based Selective Neural Network Ensemble
Neural network ensemble is a learning paradigm where several neural networks are jointly used to solve a problem. In this paper, the relationship between the generalization abilit...
Zhi-Hua Zhou, Jianxin Wu, Yuan Jiang, Shifu Chen
ICANN
2009
Springer
15 years 4 months ago
Learning from Examples to Generalize over Pose and Illumination
We present a neural system that recognizes faces under strong variations in pose and illumination. The generalization is learnt completely on the basis of examples of a subset of p...
Marco K. Müller, Rolf P. Würtz
INTERSPEECH
2010
14 years 6 months ago
Dialog prediction for a general model of turn-taking
Today there are solutions for some specific turn-taking problems, but no general model. We show how turn-taking can be reduced to two more general problems, prediction and selecti...
Nigel G. Ward, Olac Fuentes, Alejandro Vega
NN
2011
Springer
217views Neural Networks» more  NN 2011»
14 years 2 months ago
A neurodynamical model for working memory
Neurodynamical models of working memory (WM) should provide mechanisms for storing, maintaining, retrieving, and deleting information. Many models address only a subset of these a...
Razvan Pascanu, Herbert Jaeger