Kernel machine learning: a systems perspective

Abstract

The article presents a systems perspective on kernel machine learning, including a discussion of margin and generalization, support vector machines and kernels. Cost functions and dual formulation are covered including classification, regression and probability estimation. The article concludes by analysing sparsity, incremental learning and learning machines.