Second Order Dynamics Featuring Tikhonov Regularization and Time Scaling

In a Hilbert setting we aim to study a second order in time differential equation, combining viscous and Hessian-driven damping, containing a time scaling parameter function and a Tikhonov regularization term. The dynamical system is related to the problem of minimization of a nonsmooth convex function. In the formulation of the problem as well as in our analysis we use the Moreau envelope of the objective function and its gradient and heavily rely on their properties. We show that there is a setting where the newly introduced system preserves and even improves the well-known fast convergence properties of the function and Moreau envelope along the trajectories and also of the gradient of Moreau envelope due to the presence of time scaling. Moreover, in a different setting we prove strong convergence of the trajectories to the element of minimal norm from the set of all minimizers of the objective. The manuscript concludes with various numerical results.

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Publication Details

Journal
Journal of Optimization Theory and Applications
Published
2024-08-21
DOI
https://doi.org/10.1007/s10957-024-02500-8
Citations
2
Primary Topic
Numerical methods in inverse problems
Type
article
Field-Weighted Citation Impact
1.78

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article

Second Order Dynamics Featuring Tikhonov Regularization and Time Scaling

Mikhail A. Karapetyants, Ernö Robert Csetnek
2 citations
Journal of Optimization Theory and Applications
Numerical methods in inverse problems
1.78
article

Second Order Dynamics Featuring Tikhonov Regularization and Time Scaling

Mikhail A. Karapetyants, Ernö Robert Csetnek
article en
2 citations

Abstract

In a Hilbert setting we aim to study a second order in time differential equation, combining viscous and Hessian-driven damping, containing a time scaling parameter function and a Tikhonov regularization term. The dynamical system is related to the problem of minimization of a nonsmooth convex function. In the formulation of the problem as well as in our analysis we use the Moreau envelope of the objective function and its gradient and heavily rely on their properties. We show that there is a setting where the newly introduced system preserves and even improves the well-known fast convergence properties of the function and Moreau envelope along the trajectories and also of the gradient of Moreau envelope due to the presence of time scaling. Moreover, in a different setting we prove strong convergence of the trajectories to the element of minimal norm from the set of all minimizers of the objective. The manuscript concludes with various numerical results.

Journal of Optimization Theory and ApplicationsVol. 202(3)
University of Vienna (AT)
Ministerul Cercetării, Inovării şi Digitalizării, Austrian Science Fund, Universität Wien, Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii
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Numerical methods in inverse problems
1.78
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