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» A Support Vector Clustering Method
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134
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BMCBI
2010
182views more  BMCBI 2010»
15 years 3 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
143
Voted
WACV
2008
IEEE
15 years 10 months ago
Object Categorization Based on Kernel Principal Component Analysis of Visual Words
In recent years, many researchers are studying object categorization problem. It is reported that bag of keypoints approach which is based on local features without topological in...
Kazuhiro Hotta
ICMLA
2007
15 years 5 months ago
SVMotif: A Machine Learning Motif Algorithm
We describe SVMotif, a support vector machine-based learning algorithm for identification of cellular DNA transcription factor (TF) motifs extrapolated from known TF-gene interact...
Mark A. Kon, Yue Fan, Dustin T. Holloway, Charles ...
156
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TNN
2008
182views more  TNN 2008»
15 years 3 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
ISBI
2006
IEEE
16 years 4 months ago
Clustering gene expression patterns of fly embryos
The spatio-temporal patterning of gene expression in early embryos is an important source of information for understanding the functions of genes involved in development. Most ana...
Hanchuan Peng, Fuhui Long, Michael B. Eisen, Eugen...