Matrix analysis
Perturbation bounds for matrix eigenvalues
Perturbation bounds for matrix eigenvalues
Mathematical Programming: Series A and B - Special issue: Festschrift in Honor of Philip Wolfe part II: studies in nonlinear programming
Sensitivity analysis of all eigenvalues of a symmetric matrix
Numerische Mathematik
SIAM Review
Derivatives of spectral functions
Mathematics of Operations Research
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We calculate the Clarke and Michel-Penot subdifferentialsof the function which maps a symmetric matrix to its mth largesteigenvalue. We show these two subdifferentials coincide, and areidentical for all choices of index m corresponding to equaleigenvalues. Our approach is via the generalized directionalderivatives of the eigenvalue function, thereby completing earlierstudies on the classical directional derivative.