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» Two-dimensional solution path for support vector regression
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NIPS
2003
13 years 10 months ago
1-norm Support Vector Machines
The standard 2-norm SVM is known for its good performance in twoclass classi£cation. In this paper, we consider the 1-norm SVM. We argue that the 1-norm SVM may have some advanta...
Ji Zhu, Saharon Rosset, Trevor Hastie, Robert Tibs...
PRL
2011
13 years 3 months ago
A sparse version of the ridge logistic regression for large-scale text categorization
The ridge logistic regression has successfully been used in text categorization problems and it has been shown to reach the same performance as the Support Vector Machine but with...
Sujeevan Aseervatham, Anestis Antoniadis, É...
ICASSP
2008
IEEE
14 years 3 months ago
Nested support vector machines
The one-class and cost-sensitive support vector machines (SVMs) are state-of-the-art machine learning methods for estimating density level sets and solving weighted classificatio...
Gyemin Lee, Clayton Scott
ICASSP
2011
IEEE
13 years 8 days ago
Robust nonparametric regression by controlling sparsity
Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
Gonzalo Mateos, Georgios B. Giannakis
ICANN
2001
Springer
14 years 1 months ago
Sparse Kernel Regressors
Sparse kernel regressors have become popular by applying the support vector method to regression problems. Although this approach has been shown to exhibit excellent generalization...
Volker Roth