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» Co-Tracking Using Semi-Supervised Support Vector Machines
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BMCBI
2008
88views more  BMCBI 2008»
14 years 12 months ago
Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable
Background: By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Na
Myron Peto, Andrzej Kloczkowski, Vasant Honavar, R...
NIPS
2001
15 years 1 months ago
Kernel Logistic Regression and the Import Vector Machine
The support vector machine (SVM) is known for its good performance in binary classification, but its extension to multi-class classification is still an on-going research issue. I...
Ji Zhu, Trevor Hastie
WCE
2007
15 years 1 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...
CAIP
2003
Springer
184views Image Analysis» more  CAIP 2003»
15 years 5 months ago
Multi-class Support Vector Machines with Case-Based Combination for Face Recognition
Abstract. The support vector machine is basically to deal with a two-class classification problem. To get M-class classifiers for face recognition, it is common to construct a set ...
Jaepil Ko, Hyeran Byun
ICPR
2004
IEEE
16 years 29 days ago
Support Vector Machine with Local Summation Kernel for Robust Face Recognition
This paper presents Support Vector Machine (SVM) with local summation kernel for robust face recognition. In recent years, the effectiveness of SVM and local features is reported....
Kazuhiro Hotta