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ICASSP
2010
IEEE
13 years 5 months ago
Modified hierarchical clustering for sparse component analysis
The under-determined blind source separation (BSS) problem is usually solved using the sparse component analysis (SCA) technique. In SCA, the BSS is usually solved in two steps, w...
Nasser Mourad, James P. Reilly
CORR
2007
Springer
198views Education» more  CORR 2007»
13 years 10 months ago
Clustering and Feature Selection using Sparse Principal Component Analysis
In this paper, we study the application of sparse principal component analysis (PCA) to clustering and feature selection problems. Sparse PCA seeks sparse factors, or linear combi...
Ronny Luss, Alexandre d'Aspremont
CIS
2005
Springer
14 years 4 months ago
Concept Chain Based Text Clustering
Different from familiar clustering objects, text documents have sparse data spaces. A common way of representing a document is as a bag of its component words, but the semantic re...
Shaoxu Song, Jian Zhang, Chunping Li
IJON
2006
127views more  IJON 2006»
13 years 10 months ago
Sparse ICA via cluster-wise PCA
In this paper, it is shown that Independent Component Analysis (ICA) of sparse signals (sparse ICA) can be seen as a cluster-wise Principal Component Analysis (PCA). Consequently,...
Massoud Babaie-Zadeh, Christian Jutten, Ali Mansou...
SIAMSC
2008
159views more  SIAMSC 2008»
13 years 10 months ago
Hierarchical Clustering of Massive, High Dimensional Data Sets by Exploiting Ultrametric Embedding
Coding of data, usually upstream of data analysis, has crucial implications for the data analysis results. By modifying the data coding
Fionn Murtagh, Geoff Downs, Pedro Contreras