This work concentrates on optimization on Riemannian manifolds. The Limited-memory Broyden–Fletcher–Goldfarb–Shanno (LBFGS) algorithm is a commonly used quasi-Newton method for numerical optimization ...

Many machine learning applications are naturally formulated as optimization problems on Riemannian manifolds. The main idea behind Riemannian optimization is to maintain the feasibility of the ...

Preparation for Using Optimization Algorithms It is rare that a problem is submitted to an optimization algorithm "as is." By making a few changes in your problem, you can reduce its complexity, that ...

We present a method for tensor completion using optimization on low-rank matrix manifolds. Our notion of tensor-rank is based on the recently proposed framework of tensor- Singular Value Decomposition ...

This is the implementation of paper: From Constraints Fusion to Manifold Optimization: A New Directional Transport Manifold Metaheuristic Algorithm Why we study Manifold metaheuristic algorithms ...

Bilevel optimization has seen an increasing presence in various domains of applications. In this work, we propose a framework for solving bilevel optimization problems where variables of both lower ...