Spectral functions of symmetric matrices -- those depending on matrices only through their eigenvalues -- appear often in optimization. A cornerstone variational analytic tool for studying such functions is a formula relating their subdifferentials to the subdifferentials of their diagonal restrictions. This paper presents a new, short, and revealing derivation of this result. The argument has a direct analogue for spectral functions of Hermitian matrices, and for singular value functions of rectangular matrices.

Contact details are reproduced from the original publication and may be historical.

Dmitriy Drusvyatskiy

Mathematics Department, University of Washington, Seattle, WA 98195, U.S.A.

ddrusv@uw.edu

Courtney Paquette

Mathematics Department, University of Washington, Seattle, WA 98195, U.S.A.

yumiko88@uw.edu

D. Drusvyatskiy, C. Paquette. “Variational Analysis of Spectral Functions Simplified.” Journal of Convex Analysis 25 (2018), No. 1, 119–134.