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» The support vector decomposition machine
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NIPS
2003
13 years 9 months ago
Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds
The decision functions constructed by support vector machines (SVM’s) usually depend only on a subset of the training set—the so-called support vectors. We derive asymptotical...
Ingo Steinwart
AAAI
2006
13 years 9 months ago
Closest Pairs Data Selection for Support Vector Machines
This paper presents data selection procedures for support vector machines (SVM). The purpose of data selection is to reduce the dataset by eliminating as many non support vectors ...
Chaofan Sun
PRL
2006
114views more  PRL 2006»
13 years 7 months ago
Incremental training of support vector machines using hyperspheres
In the conventional incremental training of support vector machines, candidates for support vectors tend to be deleted if the separating hyperplane rotates as the training data ar...
Shinya Katagiri, Shigeo Abe
IWANN
2001
Springer
14 years 5 days ago
Non-symmetric Support Vector Machines
A novel approach to calculate the generalization error of the support vector machines and a new support vector machine–nonsymmatic support vector machine–is proposed here. Our ...
Jianfeng Feng
AVBPA
2003
Springer
140views Biometrics» more  AVBPA 2003»
14 years 29 days ago
Combining SVM Classifiers for Multiclass Problem: Its Application to Face Recognition
Abstract. In face recognition, a simple classifier such as NNk − is frequently used. For a robust system, it is common to construct the multiclass classifier by combining the out...
Jaepil Ko, Hyeran Byun