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» Introduction to artificial neural networks
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NIPS
1992
13 years 9 months ago
Explanation-Based Neural Network Learning for Robot Control
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
Tom M. Mitchell, Sebastian Thrun
GECCO
2007
Springer
174views Optimization» more  GECCO 2007»
14 years 2 months ago
Heuristic speciation for evolving neural network ensemble
Speciation is an important concept in evolutionary computation. It refers to an enhancements of evolutionary algorithms to generate a set of diverse solutions. The concept is stud...
Shin Ando
FLAIRS
2001
13 years 9 months ago
Time Series Analysis Using Unsupervised Construction of Hierarchical Classifiers
Recently we have proposed an algorithm of constructing hierarchical neural network classifiers (HNNC), that is based on a modification of error back-propagation. This algorithm co...
S. A. Dolenko, Yu. V. Orlov, I. G. Persiantsev, Ju...
ANLP
1997
84views more  ANLP 1997»
13 years 9 months ago
High Performance Segmentation of Spontaneous Speech Using Part of Speech and Trigger Word Information
We describe and experimentally evaluate an efficient method for automatically determining small clause boundaries in spontaneous speech. Our method applies an artificial neural ne...
Marsal Gavaldà, Klaus Zechner, Gregory Aist
IJON
2008
73views more  IJON 2008»
13 years 8 months ago
Third-order generalization: A new approach to categorizing higher-order generalization
Generalization, in its most basic form, is an artificial neural network's (ANN's) ability to automatically classify data that were not seen during training. This paper p...
Richard Neville