Abstract: Factorizing a low-rank matrix into two matrix factors with low dimensions from its noisy observations is a classical but challenging problem arising from real-world applications. This paper ...
Abstract: This article presents an algorithm design framework for general linearly constrained convex optimization problems. Our approach offers a flexible framework to analyze and design various ...