Binary Linear Classification and Feature Selection via Generalized Approximate Message Passing

no code implementations • 5 Jan 2014 • Justin Ziniel, Philip Schniter, Per Sederberg

For the problem of binary linear classification and feature selection, we propose algorithmic approaches to classifier design based on the generalized approximate message passing (GAMP) algorithm, recently proposed in the context of compressive sensing.

Classification Compressive Sensing +2