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JMLR
2006
389views more  JMLR 2006»
15 years 3 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,...
BMCBI
2005
112views more  BMCBI 2005»
15 years 3 months ago
Visualization methods for statistical analysis of microarray clusters
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...
BMCBI
2005
121views more  BMCBI 2005»
15 years 3 months ago
Automated methods of predicting the function of biological sequences using GO and BLAST
Background: With the exponential increase in genomic sequence data there is a need to develop automated approaches to deducing the biological functions of novel sequences with hig...
Craig E. Jones, Ute Baumann, Alfred L. Brown
KDD
2007
ACM
209views Data Mining» more  KDD 2007»
16 years 4 months ago
Temporal causal modeling with graphical granger methods
The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data...
Andrew Arnold, Yan Liu, Naoki Abe
CODES
2007
IEEE
15 years 10 months ago
A low power VLIW processor generation method by means of extracting non-redundant activation conditions
This paper proposes a low power VLIW processor generation method by automatically extracting non-redundant activation conditions of pipeline registers for clock gating. It is impo...
Hirofumi Iwato, Keishi Sakanushi, Yoshinori Takeuc...