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https://doi.org/10.1142/9789812796851_0014Cited by:8 (Source: Crossref)
Abstract:

The following sections are included:

  • Learning and Regularisation

    • Dimensionality Problems in Learning

    • Learning Functions and Complexity

    • Approaches to Complexity Control

  • Vapnik's Statistical Learning Theory

    • Consistency and Convergence of ERM

    • VC-Dimension

    • Structural Risk Minimisation

  • Support Vector Learning Machines

    • Fundamental Ideas

    • Hyperplane for Optimal Linear Separability

    • Optimal Hyperplane for Nonseparable Data

    • Pattern Recognition SVM Design

    • Summary of SVM Learning Method

  • References