Spectral Operators of Matrices: Semismoothness and Characterizations of the Generalized Jacobian

Chao Ding (Corresponding Author), Defeng Sun, Jie Sun, Kim-Chuan Toh

Research output: Journal article publicationJournal articleAcademic researchpeer-review

9 Citations (Scopus)


Spectral operators of matrices proposed recently in [C. Ding, D. F. Sun, J. Sun, and K. C. Toh, Math. Program., 168 (2018), pp. 509{531] 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 that include semidefinite programming as one of 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-order B(ouligand)-differentiability (0 < ρ≤ 1), ρ-order G-semismoothness (0 < ρ≤ 1), and characteriza- tion of generalized Jacobians.

Original languageEnglish
Pages (from-to)630-659
Number of pages30
JournalSIAM Journal on Optimization
Issue number1
Publication statusPublished - 2020


  • Generalized Jacobian
  • Matrix-valued functions
  • Semismoothness
  • Spectral operators

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science


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