We focus on the Symmetric Positive Definite (SPD) manifolds which are beneficial in various fields such as data science and statistics. This work opens a research opportunity for extension of the ...

Abstract: Recent advances suggest that encoding images through Symmetric Positive Definite (SPD) matrices and then interpreting such matrices as points on Riemannian manifolds can lead to increased ...

This repo contains 2 functions that do the same thing, one is a hand unrolled copy of the other. See my articles on my blog here and here for a more in-depth explanation. The TLDR is that since a 5x5 ...

We study several variants of decomposing a symmetric matrix into a sum of a low-rank positive semidefinite matrix and a diagonal matrix. Such decompositions have applications in factor analysis and ...

Abstract: This paper introduces a stochastic optimization-based approach to the online optimal identification of symmetric linear continuous-time systems. The identification problem is formulated as ...

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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 ...

Generating a 3 x 3 non-singular matrix with 3 non-zeroes Generated matrix: Real symmetric positive definite matrix, dimension 3x3 with 3 entries. 0: 9.9999E-01 1: -3.1031E-01 2: 3.9037E-01 This matrix ...

The constrained least-squares n × n-matrix problem where the feasibility set is the subspace of the Toeplitz matrices is analyzed. The general, the upper and lower triangular cases are solved by ...

Combination of real and imaginary parts (CRI) works well for solving complex symmetric linear systems. This paper develops a generalization of CRI method to determine the solution of Sylvester matrix ...