Online local linear classification

We present a novel convex formulation to learning binary, 2-region local linear classifiers. From this convex formulation, we formulate an online optimization scheme using stochastic gradient descent that allows for efficient training using streaming training data. We demonstrate the fast convergence and accurate classification on the canonical XOR dataset.