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» Optimization on Support Vector Machines
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TNN
2010
143views Management» more  TNN 2010»
14 years 4 months ago
Using unsupervised analysis to constrain generalization bounds for support vector classifiers
Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
Sergio Decherchi, Sandro Ridella, Rodolfo Zunino, ...
IJCNN
2006
IEEE
15 years 4 months ago
Pattern Selection for Support Vector Regression based on Sparseness and Variability
— Support Vector Machine has been well received in machine learning community with its theoretical as well as practical value. However, since its training time complexity is cubi...
Jiyoung Sun, Sungzoon Cho
COLING
2002
14 years 9 months ago
Efficient Support Vector Classifiers for Named Entity Recognition
Named Entity (NE) recognition is a task in which proper nouns and numerical information are extracted from documents and are classified into categories such as person, organizatio...
Hideki Isozaki, Hideto Kazawa
CVPR
2006
IEEE
15 years 12 months ago
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
We consider visual category recognition in the framework of measuring similarities, or equivalently perceptual distances, to prototype examples of categories. This approach is qui...
Alexander C. Berg, Hao Zhang 0003, Jitendra Malik,...
MLDM
2007
Springer
15 years 4 months ago
Nonlinear Feature Selection by Relevance Feature Vector Machine
Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...
Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yo...