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» Robustness, Risk, and Regularization in Support Vector Machi...
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PAKDD
2005
ACM
111views Data Mining» more  PAKDD 2005»
14 years 29 days 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
NIPS
2004
13 years 8 months ago
The Entire Regularization Path for the Support Vector Machine
The support vector machine (SVM) is a widely used tool for classification. Many efficient implementations exist for fitting a two-class SVM model. The user has to supply values fo...
Trevor Hastie, Saharon Rosset, Robert Tibshirani, ...
NIPS
2003
13 years 8 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
ADCM
2000
61views more  ADCM 2000»
13 years 7 months ago
Regularization Networks and Support Vector Machines
Theodoros Evgeniou, Massimiliano Pontil, Tomaso Po...