arXiv:1911.06491math.NA
What is the gradient of a scalar function of a symmetric matrix ?
Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.
Abstract
Perusal of research articles that deal with the topic of matrix calculus reveal two different approaches to calculation of the gradient of a real-valued function of a symmetric matrix leading to two different results. In the mechanics and physics communities, the gradient is calculated using the definition of a \frechet derivative, irrespective of whether the argument is symmetric or not. However, members of the statistics, economics, and electrical engineering communities use another notion of the gradient that explicitly takes into account the symmetry of the matrix, and this "symmetric gradient" $G_s$ is reported to be related to the gradient $G$ computed from the \frechet derivative with respect to a general matrix as $G_s = G + G^T - G \circ I$, where $\circ$ denotes the elementwise Hadamard product of the two matrices. We demonstrate that this relation is incorrect, and reconcile both these viewpoints by proving that $G_s = \mathrm{sym}(G)$.
> For example, the gradient of some function wrt to elements of a symmetric matrix is and should be different depending on whether the matrix is structurally symmetric Ugh. Yes and no, but mostly no. A gradient is a collection of partial derivatives. The normal meaning of…
wnoiseView on HNParent context