Academic Press Library in Signal Processing

Chapter 13

Introduction to Machine Learning

Johan A.K. Suykens,    KU Leuven, ESAT-SCD/SISTA, Leuven (Heverlee), Belgium, [e-mail]

Abstract

Considerable progress has been made in machine learning methods e.g., on the use of flexible nonlinear models, kernel-based methods, regularization techniques, sparsity, probabilistic approaches, different learning schemes and frameworks. This chapter provides a brief introduction to the machine learning section for Library in Signal Processing. The scope and context are specified and a brief overview on the chapter contributions is given.

Keywords

Machine learning; Signal processing; Learning theory; Kernel methods; Support vector machines; Neural networks; Regularization; Probabilistic ...