SSVM: A smooth support vector machine for classification

Computational Optimization and Applications

Volumn 20, Issue 1, 2001, Pages 5-22

  Lee, Yuh Jye ^a   Mangasarian, O L ^a  

^a University of Wisconsin Madison   (United States)

Author keywords

Classification; Smoothing; Support vector machines

Indexed keywords

ALGORITHMS; MATHEMATICAL PROGRAMMING; PROBLEM SOLVING; VECTORS;

SMOOTH SUPPORT VECTOR MACHINES (SSVM);

PATTERN RECOGNITION;

EID: 0035479871     PISSN: 09266003     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1011215321374     Document Type: Article

References (30)

1. Minimization of functions having Lipschitz-continuous first partial derivatives
2. Robust linear programming discrimination of two linearly inseparable sets
3. Feature selection via concave minimization and support vector machines
4. Massive data discrimination via linear support vector machines
5. A tutorial on support vector machines for pattern recognition
6. Smooth approximations to nonlinear complementarity problems
7. Smoothing methods for convex inequalities and linear complementarity problems
8. A class of smoothing functions for nonlinear and mixed complementarity problems
9. Global and superlinear convergence of the smoothing Newton method and its application to general box constrained variational inequalities
10. On homotopy-smoothing methods for variational inequalities
11. Frictional contact algorithms based on semismooth Newton methods
12. Making large-scale support vector machine learning practical
13. Solving the quadratic programming problem arising in support vector classification
14. Mathematical programming in neural networks
15. Parallel gradient distribution in unconstrained optimization
16. Generalized support vector machines
17. Massive support vector regression
18. Successive overrelaxation for support vector machines
19. Breast cancer diagnosis and prognosis via linear programming
20. Sequential minimal optimization: A fast algorithm for training support vector machines
21. Cross-validatory choice and assessment of statistical predictions
22. Analysis of a non-interior continuation method based on chen-mangasarian smoothing functions for complementarity problems