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ICANN
2007
Springer
14 years 4 months ago
Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space
Abstract. In this paper we discuss sparse least squares support vector regressors (sparse LS SVRs) defined in the reduced empirical feature space, which is a subspace of mapped tr...
Shigeo Abe, Kenta Onishi
BMCBI
2008
138views more  BMCBI 2008»
13 years 10 months ago
Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction
Background: We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represent...
Ching-Wai Tan, David T. Jones
INFORMATICALT
2007
123views more  INFORMATICALT 2007»
13 years 9 months ago
Design and Implementation of Parallel Counterpropagation Networks Using MPI
The objective of this research is to construct parallel models that simulate the behavior of artificial neural networks. The type of network that is simulated in this project is t...
Athanasios Margaris, Stavros Souravlas, Efthimios ...
IJCNN
2006
IEEE
14 years 3 months ago
Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...
NN
2006
Springer
13 years 9 months ago
Propagation and control of stochastic signals through universal learning networks
The way of propagating and control of stochastic signals through Universal Learning Networks (ULNs) and its applications are proposed. ULNs have been already developed to form a s...
Kotaro Hirasawa, Shingo Mabu, Jinglu Hu