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» On Feature Selection through Clustering
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ICTAI
2010
IEEE
13 years 5 months ago
Unsupervised Greedy Learning of Finite Mixture Models
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
CCGRID
2006
IEEE
14 years 1 months ago
A Failure-Aware Scheduling Strategy in Large-Scale Cluster System
As the scale is expanding, node failure becomes a commonplace feature of large-scale cluster systems. As an important part of cluster operating system software, job scheduling tak...
Linping Wu, Dan Meng, Jianfeng Zhan, Wang Lei, Bib...
WCRE
2006
IEEE
14 years 1 months ago
On Computing the Canonical Features of Software Systems
Software applications typically have many features that vary in their similarity. We define a measurement of similarity between pairs of features based on their underlying implem...
Jay Kothari, Trip Denton, Spiros Mancoridis, Ali S...
ISMIR
2005
Springer
179views Music» more  ISMIR 2005»
14 years 1 months ago
Databionic Visualization of Music Collections According to Perceptual Distance
We describe the MusicMiner system for organizing large collections of music with databionic mining techniques. Low level audio features are extracted from the raw audio data on sh...
Fabian Mörchen, Alfred Ultsch, Mario Nöc...
BMCBI
2005
190views more  BMCBI 2005»
13 years 7 months ago
An Entropy-based gene selection method for cancer classification using microarray data
Background: Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of n...
Xiaoxing Liu, Arun Krishnan, Adrian Mondry