In this lecture, we will a look at the dual formulation of the SVM objective and kernels as a method to train non-linear models. We will see examples of the kernel trick in action
Chapters 3 and 6 of Hal Daumé III, A Course in Machine Learning
Chapters 14, 15, 16 of Shai Shalev-Shwartz and Shai Ben-David, Understanding Machine Learning: From Theory to Algorithms (Available online)
A talk on Optimization, Support Vector Machines, and Machine Learning that goes into the details of primal and dual forms of SVMs and optimization.