Abstract: Symmetric Positive Definite (SPD) matrices have received wide attention in machine learning due to their intrinsic capacity to encode underlying structural correlation in data. Many ...

Positive definite matrices play a central role in mathematics, physics, statistics and engineering due to their unique properties and widespread applicability. These matrices, which are characterised ...

first I want to thank you for your great work and your very good explanations series in YT. I encounter a problem when trying to estimate a adjacency matrix from ...

Abstract: Many signal processing and machine learning applications are framed as constrained optimization problems with positive definite constraints. Important examples include kernel matrix learning ...

ABSTRACT: We derive necessary and sufficient conditions for the existence of a Hermitian nonnegative-definite solution to the matrix equation AXB = C. Moreover, we derive a representation of a general ...

Center for Research and Development in Mathematics and Applications, Department of Mathematics, University of Aveiro, Aveiro, Portugal. Department of Mathematics, Faculty of Science and Technology, ...