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» Identifying Clusters from Positive Data
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ICIAP
2005
ACM
14 years 10 months ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti...
LAWEB
2006
IEEE
14 years 4 months ago
Analysis of Web Search Engine Clicked Documents
In this paper we process and analyze web search engine query and click data from the perspective of the documents (URL’s) selected. We initially define possible document categor...
David F. Nettleton, Liliana Calderón-Benavi...
DAGSTUHL
2009
13 years 11 months ago
Learning Highly Structured Manifolds: Harnessing the Power of SOMs
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
Erzsébet Merényi, Kadim Tasdemir, Li...
SAC
2004
ACM
14 years 3 months ago
Time-frequency feature detection for time-course microarray data
Gene clustering based on microarray data provides useful functional information to the working biologists. Many current gene-clustering algorithms rely on Euclidean-based distance...
Jiawu Feng, Paolo Emilio Barbano, Bud Mishra
BMCBI
2008
135views more  BMCBI 2008»
13 years 10 months ago
Identification of a small optimal subset of CpG sites as bio-markers from high-throughput DNA methylation profiles
Background: DNA methylation patterns have been shown to significantly correlate with different tissue types and disease states. High-throughput methylation arrays enable large-sca...
Hailong Meng, Edward Lenn Murrelle, Guoya Li