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JMLR
2006
389views more  JMLR 2006»
15 years 1 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
2007
164views more  BMCBI 2007»
15 years 1 months ago
SEARCHPATTOOL: a new method for mining the most specific frequent patterns for binding sites with application to prokaryotic DNA
Background: Computational methods to predict transcription factor binding sites (TFBS) based on exhaustive algorithms are guaranteed to find the best patterns but are often limite...
Fathi Elloumi, Martha Nason
JMLR
2002
111views more  JMLR 2002»
15 years 27 days ago
The Learning-Curve Sampling Method Applied to Model-Based Clustering
We examine the learning-curve sampling method, an approach for applying machinelearning algorithms to large data sets. The approach is based on the observation that the computatio...
Christopher Meek, Bo Thiesson, David Heckerman
BMCBI
2011
14 years 7 months ago
Analysis on the reconstruction accuracy of the Fitch method for inferring ancestral states
Background: As one of the most widely used parsimony methods for ancestral reconstruction, the Fitch method minimizes the total number of hypothetical substitutions along all bran...
Jialiang Yang, Jun Li, Liuhuan Dong, Stefan Gr&uum...
ATAL
2003
Springer
15 years 6 months ago
A method for decentralized clustering in large multi-agent systems
This paper examines a method of clustering within a fully decentralized multi-agent system. Our goal is to group agents with similar objectives or data, as is done in traditional ...
Elth Ogston, Benno J. Overeinder, Maarten van Stee...