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CORR
2008
Springer
113views Education» more  CORR 2008»
14 years 10 months ago
Robustness, Risk, and Regularization in Support Vector Machines
We consider two new formulations for classification problems in the spirit of support vector machines based on robust optimization. Our formulations are designed to build in prote...
Huan Xu, Shie Mannor, Constantine Caramanis
KES
2000
Springer
15 years 1 months ago
Multi-view face detection using support vector machines and eigenspace modelling
An approach to multi-view face detection based on head pose estimation is presented in this paper. Support Vector Regression is employed to solve the problem of pose estimation. T...
Yongmin Li, Shaogang Gong, Jamie Sherrah, Heather ...
CORR
2008
Springer
142views Education» more  CORR 2008»
14 years 10 months ago
A Gaussian Belief Propagation Solver for Large Scale Support Vector Machines
Support vector machines (SVMs) are an extremely successful type of classification and regression algorithms. Building an SVM entails solving a constrained convex quadratic program...
Danny Bickson, Elad Yom-Tov, Danny Dolev
FSS
2007
102views more  FSS 2007»
14 years 10 months ago
Extraction of fuzzy rules from support vector machines
The relationship between support vector machines (SVMs) and Takagi–Sugeno–Kang (TSK) fuzzy systems is shown. An exact representation of SVMs as TSK fuzzy systems is given for ...
Juan Luis Castro, L. D. Flores-Hidalgo, Carlos Jav...
IDEAL
2010
Springer
14 years 7 months ago
Robust 1-Norm Soft Margin Smooth Support Vector Machine
Based on studies and experiments on the loss term of SVMs, we argue that 1-norm measurement is better than 2-norm measurement for outlier resistance. Thus, we modify the previous 2...
Li-Jen Chien, Yuh-Jye Lee, Zhi-Peng Kao, Chih-Chen...