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» A kernel path algorithm for support vector machines
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ISBI
2008
IEEE
14 years 9 months ago
Support vector machine for data on manifolds: An application to image analysis
The Support Vector Machine (SVM) is a powerful tool for classification. We generalize SVM to work with data objects that are naturally understood to be lying on curved manifolds, ...
Suman K. Sen, Mark Foskey, James Stephen Marron, M...
CSB
2005
IEEE
133views Bioinformatics» more  CSB 2005»
14 years 2 months ago
Investigation into Biomedical Literature Classification Using Support Vector Machines
Specific topic search in the PubMed Database, one of the most important information resources for scientific community, presents a big challenge to the users. The researcher typic...
Nalini Polavarapu, Shamkant B. Navathe, Ramprasad ...
ICASSP
2008
IEEE
14 years 3 months ago
Hybrid feature selection for gesture recognition using support vector machines
This paper presents an approach for a multi-cue based two-dimensional gesture recognition that combines two different forms of cues, namely shape cues and motion cues, in a suppor...
Yu Yuan, Kenneth Barner
NIPS
2003
13 years 10 months ago
Phonetic Speaker Recognition with Support Vector Machines
A recent area of significant progress in speaker recognition is the use of high level features—idiolect, phonetic relations, prosody, discourse structure, etc. A speaker not on...
William M. Campbell, Joseph P. Campbell, Douglas A...
PAKDD
2005
ACM
111views Data Mining» more  PAKDD 2005»
14 years 2 months ago
Training Support Vector Machines Using Greedy Stagewise Algorithm
Abstract. Hard margin support vector machines (HM-SVMs) have a risk of getting overfitting in the presence of the noise. Soft margin SVMs deal with this
Liefeng Bo, Ling Wang, Licheng Jiao