Learning Theory: An Approximation Theory Viewpoint
暂无分享,去创建一个
Preface Foreword 1. The framework of learning 2. Basic hypothesis spaces 3. Estimating the sample error 4. Polynomial decay approximation error 5. Estimating covering numbers 6. Logarithmic decay approximation error 7. On the bias-variance problem 8. Regularization 9. Support vector machines for classification 10. General regularized classifiers Bibliography Index.