DC semidefinite programming and cone constrained DC optimization II: local search methods

Долгополик, М. В.

doi:10.1007/s10589-023-00479-y

Comput Optim Appl

2023

DOI: 10.1007/s10589-023-00479-y

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DC semidefinite programming and cone constrained DC optimization II: local search methods

М. В. Долгополик

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2024

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Cited by 2 publications

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Subdifferentials of convex matrix-valued functions

Dolgopolik

2024

Optim Lett

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Subdifferentials of convex matrix-valued functions

Dolgopolik

2024

Optim Lett

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Convexity of nonlinear mappings between bounded linear operator spaces

Bounkhel,

Al-Tane

2024

MATH

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<abstract><p>Motivated by the work <sup>[<xref ref-type="bibr" rid="b7">7</xref>]</sup>, in which the author studied the convexity of nonlinear mappings defined between bounded linear operator spaces, our research extends this inquiry. In this work, we continue the study of the convexity of nonlinear mappings defined between bounded linear operator spaces and we establish a characterization in terms of the second order directional derivative. We apply the main result to prove the convexity and the nonconvexity of well-known nonlinear mappings. The case of nondifferentiable mappings is also treated in the last section.</p></abstract>

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DC semidefinite programming and cone constrained DC optimization II: local search methods

Cited by 2 publications

References 48 publications

Subdifferentials of convex matrix-valued functions

Subdifferentials of convex matrix-valued functions

Convexity of nonlinear mappings between bounded linear operator spaces

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