Evaluation complexity of algorithms for nonconvex optimization

Coralia Cartis, Nicholas Ian Mark Gould, Philippe TOINT

Namur Institute for Complex Systems

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31 Article
7 Papier de travail
2 Autre rapport
1 Chapitre
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7 résultats

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2024
Refining asymptotic complexity bounds for nonconvex optimization methods, including why steepest descent is o(eps^{-2}) rather than O(eps^{-2})
Gratton, S., Sim, C. & Toint, P., 20 août 2024, Arxiv.
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2023
Yet another fast variant of Newton's method for nonconvex optimization
Gratton, S., Jerad, S. & TOINT, P., 21 févr. 2023, Arxiv, 26 p.
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2022
First-Order Objective-Function-Free Optimization Algorithms and Their Complexity
Gratton, S., Jerad, S. & TOINT, P., 7 mars 2022, Arxiv.
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2020
Strong Evaluation Complexity Bounds for Arbitrary-Order Optimization of Nonconvex Nonsmooth Composite Functions
Cartis, C., Gould, N. & Toint, P., 30 janv. 2020, Arxiv.
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2015
Improved worst-case evaluation complexity for potentially rank-deficient nonlinear least-Euclidean-norm problems using higher-order regularized models
Cartis, C., Gould, N. I. M. & Toint, P., 18 nov. 2015, 18 p. (naXys technical report).
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Worst-case evaluation complexity for unconstrained nonlinear optimization using high-order regularized models
Birgin, E., Gardenghi, J., Martinez, J.-M., Santos, S. A. & Toint, P., juin 2015, 2015: Namur center for complex systems, 8 p. (naXys Technical Reports; Vol 05-2015).
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2013
An example of slow convergence for Newton's method on a function with globally Lipschitz continuous Hessian
Cartis, C., Gould, N. I. M. & Toint, P., 5 mai 2013, Namur center for complex systems, 9 p.
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Evaluation complexity of algorithms for nonconvex optimization

Résultat de recherche

Résultats de recherche

Refining asymptotic complexity bounds for nonconvex optimization methods, including why steepest descent is o(eps^{-2}) rather than O(eps^{-2})

Yet another fast variant of Newton's method for nonconvex optimization

First-Order Objective-Function-Free Optimization Algorithms and Their Complexity

Strong Evaluation Complexity Bounds for Arbitrary-Order Optimization of Nonconvex Nonsmooth Composite Functions

Improved worst-case evaluation complexity for potentially rank-deficient nonlinear least-Euclidean-norm problems using higher-order regularized models

Worst-case evaluation complexity for unconstrained nonlinear optimization using high-order regularized models

An example of slow convergence for Newton's method on a function with globally Lipschitz continuous Hessian