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Title: Spectral operators of matrices : semismoothness and characterizations of the generalized Jacobian
Authors: Ding, C
Sun, D 
Sun, J
Toh, KC
Issue Date: 2020
Source: SIAM journal on optimization, 2020, v. 30, no. 1, p. 630-659
Abstract: 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.
Keywords: Spectral operators
Matrix-valued functions
Semismoothness
Generalized Jacobian
Publisher: Society for Industrial and Applied Mathematics
Journal: SIAM journal on optimization 
ISSN: 1052-6234
EISSN: 1095-7189
DOI: 10.1137/18M1222235
Rights: © 2020 Society for Industrial and Applied Mathematics
The following publication Ding, C., Sun, D., Sun, J., & Toh, K. C. (2020). Spectral operators of matrices: semismoothness and characterizations of the generalized Jacobian. SIAM Journal on Optimization, 30(1), 630-659 is available at https://doi.org/10.1137/18M1222235.
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