Scott E. Fahlman, Christian Lebiere  Home/Search
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Abstract: Cascade-Correlation is a new architecture and supervised learning algorithm for artificial neural networks. Instead of just adjusting the weights in a network of fixed topology, Cascade-Correlation begins with a minimal network, then automatically trains and adds new hidden units one by one, creating a multi-layer structure. Once a new hidden unit has been added to the network, its input-side weights are frozen. This unit then becomes a permanent feature-detector in the network, available for... (Update)
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BibTeX entry: (Update)
S. E. Fahlman and C. Lebiere. The cascade-correlation learning architecture. Technical Report CMU-CS-90-100, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 1990. http://citeseer.ist.psu.edu/fahlman90cascadecorrelation.html More
@inproceedings{ fahlman90cascadecorrelation,
author = "S. E. Fahlman and C. Lebiere",
title = "The Cascade-Correlation Learning Architecture",
booktitle = "Advances in Neural Information Processing Systems",
volume = "2",
publisher = "Morgan Kaufmann, San Mateo",
address = "Denver 1989",
editor = "D. S. Touretzky",
pages = "524--532",
year = "1990",
url = "citeseer.ist.psu.edu/fahlman90cascadecorrelation.html" }
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