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ESANN
2003
13 years 6 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...
JAIR
2002
163views more  JAIR 2002»
13 years 4 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
JMLR
2006
389views more  JMLR 2006»
13 years 4 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...
FLAIRS
2004
13 years 6 months ago
Gene Expression Data Classification with Revised Kernel Partial Least Squares Algorithm
One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
ZhenQiu Liu, Dechang Chen
IWANN
2001
Springer
13 years 9 months ago
Learning Adaptive Parameters with Restricted Genetic Optimization Method
Abstract. Mechanisms for adapting models, filters, regulators and so on to changing properties of a system are of fundamental importance in many modern identification, estimation...
Santiago Garrido, Luis Moreno