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» Properties of Support Vector Machines
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NIPS
2003
14 years 10 months ago
Margin Maximizing Loss Functions
Margin maximizing properties play an important role in the analysis of classi£cation models, such as boosting and support vector machines. Margin maximization is theoretically in...
Saharon Rosset, Ji Zhu, Trevor Hastie
NIPS
2003
14 years 10 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
14 years 11 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»
14 years 9 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
15 years 1 months 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