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ISMB
1993
15 years 1 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»
14 years 11 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»
15 years 5 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»
15 years 3 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
13 years 2 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...