Theory of SVM and programming based learning algorithms in neural networks

Jisuanji Xuebao/Chinese Journal of Computers

Volumn 24, Issue 2, 2001, Pages 113-118

  Zhang, L ^a  

^a ANHUI UNIVERSITY   (China)

Author keywords

Learning algorithm; Neural network; Programming; Support vector machine

Indexed keywords

LEARNING ALGORITHMS; MATHEMATICAL PROGRAMMING;

LINEAR SEPARABILITY; PROGRAMMING BASED ALGORITHM; SUPPORT RECTOR MACHINE; VAPNIK;

NEURAL NETWORKS;

EID: 0035242302     PISSN: 02544164     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (17)

1. An overview of statistical learning theory
2. Input space versus feature space in kernel-based methods
3. A tutorial on support vector machine for pattern recognition
4. Support vector machine for spam categorization
5. A tutorial on support vector regression
6. Support vector method for function approximation, regression, and signal processing
7. Adaptive margin vector machines for classification
8. Simple and robust methods for support vector machine classifiers
9. Nonlinear component analysis as a Kernel eigenvalue problem
10. Improving support vector machine classifier by modifying Kernel functions
11. Programming based learning algorithm of neural networks with self-feedback connections
12. Programming based learning algorithm of neural networks
13. A geometrical representation of McCulloch-Pitts neural model and its applications
14. Algorithms for the solution of quadratic knapsack problems