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JMLR
2006
389views more  JMLR 2006»
15 years 6 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,...
JUCS
2010
215views more  JUCS 2010»
15 years 1 months ago
A Multidisciplinary Survey of Computational Techniques for the Modelling, Simulation and Analysis of Biochemical Networks
: All processes of life are controlled by networks of interacting biochemical components. The purpose of modelling these networks is manifold. From a theoretical point of view it a...
James Decraene, Thomas Hinze
IPPS
2010
IEEE
15 years 4 months ago
KRASH: Reproducible CPU load generation on many-core machines
Abstract--In this article we present KRASH, a tool for reproducible generation of system-level CPU load. This tool is intended for use in shared memory machines equipped with multi...
Swann Perarnau, Guillaume Huard
BMCBI
2010
96views more  BMCBI 2010»
15 years 6 months ago
OpenChrom: a cross-platform open source software for the mass spectrometric analysis of chromatographic data
Background: Today, data evaluation has become a bottleneck in chromatographic science. Analytical instruments equipped with automated samplers yield large amounts of measurement d...
Philip Wenig, Juergen Odermatt
GLOBECOM
2010
IEEE
15 years 4 months ago
Cognitive Network Inference through Bayesian Network Analysis
Cognitive networking deals with applying cognition to the entire network protocol stack for achieving stack-wide as well as network-wide performance goals, unlike cognitive radios ...
Giorgio Quer, Hemanth Meenakshisundaram, Tamma Bhe...