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ESANN
2003
13 years 9 months ago
Accelerating the convergence speed of neural networks learning methods using least squares
In this work a hybrid training scheme for the supervised learning of feedforward neural networks is presented. In the proposed method, the weights of the last layer are obtained em...
Oscar Fontenla-Romero, Deniz Erdogmus, José...
BMCBI
2006
175views more  BMCBI 2006»
13 years 7 months ago
Parameter estimation for stiff equations of biosystems using radial basis function networks
Background: The modeling of dynamic systems requires estimating kinetic parameters from experimentally measured time-courses. Conventional global optimization methods used for par...
Yoshiya Matsubara, Shinichi Kikuchi, Masahiro Sugi...
JMLR
2008
94views more  JMLR 2008»
13 years 7 months ago
Using Markov Blankets for Causal Structure Learning
We show how a generic feature selection algorithm returning strongly relevant variables can be turned into a causal structure learning algorithm. We prove this under the Faithfuln...
Jean-Philippe Pellet, André Elisseeff
INFOCOM
2008
IEEE
14 years 2 months ago
A Distributed Optimization Algorithm for Multi-Hop Cognitive Radio Networks
Cognitive radio (CR) is a revolution in radio technology and is viewed as an enabling technology for dynamic spectrum access. This paper investigates how to design distributed alg...
Yi Shi, Y. Thomas Hou
TNN
2008
181views more  TNN 2008»
13 years 7 months ago
Optimized Approximation Algorithm in Neural Networks Without Overfitting
In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...
Yinyin Liu, Janusz A. Starzyk, Zhen Zhu