Regularizer design for structured learning
Design and analysis of tractable methods for estimation of structured models from massive high-dimensional datasets has been a topic of research in statistics, machine learning and engineering for many years. Regularization, the idea of simultaneously optimizing a data fidelity term (loss) and a structure-promoting term (regularizer), is a widely used …