First order inertial optimization algorithms with threshold effects associated with dry friction

نویسندگان

چکیده

In a Hilbert space setting, we consider new first order optimization algorithms which are obtained by temporal discretization of damped inertial autonomous dynamic involving dry friction. The function f to be minimized is assumed differentiable (not necessarily convex). friction potential $$ \varphi , has sharp minimum at the origin, enters algorithm via its proximal mapping, acts as soft thresholding operator on sum velocity and gradient terms. After finite number steps, structure changes, losing character become steepest descent method. geometric damping driven Hessian makes it possible control attenuate oscillations. generates convergent sequences when convex, in nonconvex case satisfies Kurdyka–Lojasiewicz property. convergence results robust with respect numerical errors, perturbations. study then extended nonsmooth convex f, involves operators $$\varphi separately. Applications given Lasso problem d.c. programming.

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ژورنال

عنوان ژورنال: Computational Optimization and Applications

سال: 2023

ISSN: ['0926-6003', '1573-2894']

DOI: https://doi.org/10.1007/s10589-023-00509-9