Machine learning has undergone rapid growth in diversification and practicality, and the repertoire of techniques has evolved and expanded. The aim of this book

The book covers theoretical questions including the latest extension of the formalism, and computational issues and focuses on some of the more fruitful and pro

A detailed overview of current research in kernel methods and their application to computational biology.

Reproducing kernel Hilbert spaces are elucidated without assuming prior familiarity with Hilbert spaces. Compared with extant pedagogic material, greater care i

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, opti