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» Hierarchical Convex NMF for Clustering Massive Data
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JMLR
2010
175views more  JMLR 2010»
12 years 11 months ago
Hierarchical Convex NMF for Clustering Massive Data
We present an extension of convex-hull non-negative matrix factorization (CH-NMF) which was recently proposed as a large scale variant of convex non-negative matrix factorization ...
Kristian Kersting, Mirwaes Wahabzada, Christian Th...

Publication
197views
12 years 25 days ago
Convex non-negative matrix factorization for massive datasets
Non-negative matrix factorization (NMF) has become a standard tool in data mining, information retrieval, and signal processing. It is used to factorize a non-negative data matrix ...
C. Thurau, K. Kersting, M. Wahabzada, and C. Bauck...
ICDM
2009
IEEE
126views Data Mining» more  ICDM 2009»
13 years 11 months ago
Convex Non-negative Matrix Factorization in the Wild
Abstract—Non-negative matrix factorization (NMF) has recently received a lot of attention in data mining, information retrieval, and computer vision. It factorizes a non-negative...
Christian Thurau, Kristian Kersting, Christian Bau...
BMCBI
2006
119views more  BMCBI 2006»
13 years 4 months ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs
SIAMSC
2008
159views more  SIAMSC 2008»
13 years 4 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