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JMLR
2008
104views more  JMLR 2008»
15 years 3 months ago
Nearly Uniform Validation Improves Compression-Based Error Bounds
This paper develops bounds on out-of-sample error rates for support vector machines (SVMs). The bounds are based on the numbers of support vectors in the SVMs rather than on VC di...
Eric Bax
JMLR
2010
119views more  JMLR 2010»
14 years 10 months ago
The Group Dantzig Selector
We introduce a new method -- the group Dantzig selector -- for high dimensional sparse regression with group structure, which has a convincing theory about why utilizing the group...
Han Liu, Jian Zhang 0003, Xiaoye Jiang, Jun Liu
ICML
2005
IEEE
16 years 4 months ago
The cross entropy method for classification
We consider support vector machines for binary classification. As opposed to most approaches we use the number of support vectors (the "L0 norm") as a regularizing term ...
Shie Mannor, Dori Peleg, Reuven Y. Rubinstein
PAKDD
2007
ACM
128views Data Mining» more  PAKDD 2007»
15 years 10 months ago
Selecting a Reduced Set for Building Sparse Support Vector Regression in the Primal
Recent work shows that Support vector machines (SVMs) can be solved efficiently in the primal. This paper follows this line of research and shows how to build sparse support vector...
Liefeng Bo, Ling Wang, Licheng Jiao
NIPS
2000
15 years 5 months ago
Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra
A system has been developed to extract diagnostic information from jet engine carcass vibration data. Support Vector Machines applied to novelty detection provide a measure of how...
Paul Hayton, Bernhard Schölkopf, Lionel Taras...