Symmetric matrices of huge size with many zero entries, called sparse symmetric matrices, are nowadays studied actively in the context of artificial intelligence and data science. One of the efficient ...

Riemannian geometry offers an elegant mathematical framework for the analysis of data that naturally resides on curved spaces, particularly the manifold of symmetric positive definite (SPD) matrices.

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 ...