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 ...

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 ...

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 ...

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, ...

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 ...