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BMCBI
2006
119views more  BMCBI 2006»
13 years 8 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
BMCBI
2004
208views more  BMCBI 2004»
13 years 8 months ago
Hybrid clustering for microarray image analysis combining intensity and shape features
Background: Image analysis is the first crucial step to obtain reliable results from microarray experiments. First, areas in the image belonging to single spots have to be identif...
Jörg Rahnenführer, Daniel Bozinov
KDD
2007
ACM
231views Data Mining» more  KDD 2007»
14 years 9 months ago
Xproj: a framework for projected structural clustering of xml documents
XML has become a popular method of data representation both on the web and in databases in recent years. One of the reasons for the popularity of XML has been its ability to encod...
Charu C. Aggarwal, Na Ta, Jianyong Wang, Jianhua F...
ICCV
2005
IEEE
14 years 10 months ago
Local Features for Object Class Recognition
In this paper we compare the performance of local detectors and descriptors in the context of object class recognition. Recently, many detectors / descriptors have been evaluated ...
Krystian Mikolajczyk, Bastian Leibe, Bernt Schiele
COMPGEOM
2006
ACM
14 years 2 months ago
A fast k-means implementation using coresets
In this paper we develop an efficient implementation for a k-means clustering algorithm. The novel feature of our algorithm is that it uses coresets to speed up the algorithm. A ...
Gereon Frahling, Christian Sohler