Riemannian preconditioned coordinate descent for low multi-linear rank approximation
Mohammad Hamed Firouzehtarash,
Reshad Hosseini
Abstract:This paper presents a fast, memory efficient, optimization-based, first-order method for low multi-linear rank approximation of high-order, high-dimensional tensors. In our method, we exploit the second-order information of the cost function and the constraints to suggest a new Riemannian metric on the Grassmann manifold. We use a Riemmanian coordinate descent method for solving the problem, and also provide a local convergence analysis matching that of the coordinate descent method in the Euclidean setting. W… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.