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» Learning the Common Structure of Data
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150
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BMCBI
2005
151views more  BMCBI 2005»
15 years 3 months ago
stam - a Bioconductor compliant R package for structured analysis of microarray data
Background: Genome wide microarray studies have the potential to unveil novel disease entities. Clinically homogeneous groups of patients can have diverse gene expression profiles...
Claudio Lottaz, Rainer Spang
146
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ICDM
2005
IEEE
188views Data Mining» more  ICDM 2005»
15 years 9 months ago
Hierarchy-Regularized Latent Semantic Indexing
Organizing textual documents into a hierarchical taxonomy is a common practice in knowledge management. Beside textual features, the hierarchical structure of directories reflect...
Yi Huang, Kai Yu, Matthias Schubert, Shipeng Yu, V...
118
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CICLING
2010
Springer
15 years 10 months ago
Computational Models of Language Acquisition
Abstract. Child language acquisition, one of Nature’s most fascinating phenomena, is to a large extent still a puzzle. Experimental evidence seems to support the view that early ...
Shuly Wintner
192
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ASC
2007
15 years 3 months ago
Unsupervised learning with normalised data and non-Euclidean norms
The measurement of distance is one of the key steps in the unsupervised learning process, as it is through these distance measurements that patterns and correlations are discovere...
Kevin Doherty, Rod Adams, Neil Davey
132
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NECO
1998
119views more  NECO 1998»
15 years 3 months ago
Density Estimation by Mixture Models with Smoothing Priors
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...
Akio Utsugi