Machine Learning

CS 5350/6350, DS 4350, Spring 2024

Support Vector Machines

In this lecture, we will look at support vector machines. We will first look at the connection between maximizing margins and learning linear classifiers. This will give us an objective function for training, namely the SVM objective. This objective is our first sight of the idea of regularized risk minimization.

There are several algorithms for optimizing the SVM objective. We will look at a simple, yet effective, one: stochastic sub-gradient descent and explore the connection with the perceptron algorithm.



Additional reading