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ISMB
1993
13 years 9 months ago
Protein Classification Using Neural Networks
Wehave recently described a method based on Artificial Neural Networksto cluster protein sequences into families. The network was trained with Kohonen’s unsupervised-learning al...
Edgardo A. Ferrán, Pascual Ferrara, Bernard...
VLSISP
2002
124views more  VLSISP 2002»
13 years 7 months ago
Agglomerative Learning Algorithms for General Fuzzy Min-Max Neural Network
In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...
Bogdan Gabrys
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
14 years 1 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
EUROGP
2004
Springer
170views Optimization» more  EUROGP 2004»
13 years 11 months ago
Comparing Hybrid Systems to Design and Optimize Artificial Neural Networks
Abstract. In this paper we conduct a comparative study between hybrid methods to optimize multilayer perceptrons: a model that optimizes the architecture and initial weights of mul...
Pedro A. Castillo Valdivieso, Maribel Garcí...
CVPR
2012
IEEE
11 years 10 months ago
Image denoising: Can plain neural networks compete with BM3D?
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with c...
Harold Christopher Burger, Christian J. Schuler, S...