English

Spectral operators of matrices: semismoothness and characterizations of the generalized Jacobian

Optimization and Control 2018-10-24 v1

Abstract

Spectral operators of matrices proposed recently in [C. Ding, D.F. Sun, J. Sun, and K.C. Toh, Math. Program. {\bf 168}, 509--531 (2018)] are a class of matrix valued functions, which map matrices to matrices by applying a vector-to-vector function to all eigenvalues/singular values of the underlying matrices. Spectral operators play a crucial role in the study of various applications involving matrices such as matrix optimization problems (MOPs) {that include semidefinite programming as one of the most important example classes}. In this paper, we will study more fundamental first- and second-order properties of spectral operators, including the Lipschitz continuity, ρ\rho-order B(ouligand)-differentiability (0<ρ10<\rho\le 1), ρ\rho-order G-semismoothness (0<ρ10<\rho\le 1), and characterization of generalized Jacobians.

Keywords

Cite

@article{arxiv.1810.09856,
  title  = {Spectral operators of matrices: semismoothness and characterizations of the generalized Jacobian},
  author = {Chao Ding and Defeng Sun and Jie Sun and Kim-Chuan Toh},
  journal= {arXiv preprint arXiv:1810.09856},
  year   = {2018}
}

Comments

25 pages. arXiv admin note: substantial text overlap with arXiv:1401.2269