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Complexity of trust-region methods with potentially unbounded Hessian approximations for smooth and nonsmooth optimization

Geoffroy Leconte & Dominique Orban

Mathematical Programming2026https://doi.org/10.1007/s10107-025-02304-2article
AJG 4
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0.44

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https://doi.org/https://doi.org/10.1007/s10107-025-02304-2

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@article{geoffroy2026,
  title        = {{Complexity of trust-region methods with potentially unbounded Hessian approximations for smooth and nonsmooth optimization}},
  author       = {Geoffroy Leconte & Dominique Orban},
  journal      = {Mathematical Programming},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s10107-025-02304-2},
}

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Complexity of trust-region methods with potentially unbounded Hessian approximations for smooth and nonsmooth optimization

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Evidence weight

0.44

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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