Cover Image

A proximal-gradient inertial algorithm with Tikhonov regularization: strong convergence to the minimal norm solution

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	László, Szilárd Csaba
Format:	Preprint
Published:	2024
Subjects:	Optimization and Control Numerical Analysis 34G25, 47J25, 47H05, 90C26, 90C30, 65K10
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On the convergence of an inertial proximal algorithm with a Tikhonov regularization term
by: László, Szilárd Csaba
Published: (2023)

Solving convex optimization problems via a second order dynamical system with implicit Hessian damping and Tikhonov regularization
by: László, Szilárd Csaba
Published: (2024)

On the convergence of adaptive first order methods: proximal gradient and alternating minimization algorithms
by: Latafat, Puya, et al.
Published: (2023)

Adaptive proximal algorithms for convex optimization under local Lipschitz continuity of the gradient
by: Latafat, Puya, et al.
Published: (2023)

Adaptive proximal gradient methods are universal without approximation
by: Oikonomidis, Konstantinos A., et al.
Published: (2024)

Tikhonov regularization of monotone operator flows not only ensures strong convergence of the trajectories but also speeds up the vanishing of the residuals
by: Bot, Radu Ioan, et al.
Published: (2024)

Complexity-optimal and parameter-free first-order methods for finding stationary points of composite optimization problems
by: Kong, Weiwei
Published: (2022)

Solving nonconvex optimization problems via a second order dynamical system with unbounded damping
by: László, Szilárd Csaba
Published: (2025)

A robust regularized extreme learning machine for regression problems based on self-adaptive accelerated extra-gradient algorithm
by: Adegoke, Muideen, et al.
Published: (2024)

Relaxed and inertial nonlinear Forward-Backward algorithm
by: Maulén, Juan José, et al.
Published: (2025)

A first-order method for nonconvex-strongly-concave constrained minimax optimization
by: Lu, Zhaosong, et al.
Published: (2025)

Strong convergence and fast rates for systems with Tikhonov regularization
by: Csetnek, Ernö Robert, et al.
Published: (2024)

On the convergence of proximal gradient methods for convex simple bilevel optimization
by: Latafat, Puya, et al.
Published: (2023)

Fast Reflected Forward-Backward algorithm: achieving fast convergence rates for convex optimization with linear cone constraints
by: Bot, Radu Ioan, et al.
Published: (2024)

Bounding-Focused Discretization Methods for the Global Optimization of Nonconvex Semi-Infinite Programs
by: Turan, Evren M., et al.
Published: (2023)

Multivariate approximation by polynomial and generalised rational functions
by: Millán, R. Díaz, et al.
Published: (2021)

Splitting Algorithms for Distributionally Robust Optimization
by: Briceño-Arias, Luis, et al.
Published: (2024)

Entropic Mirror Descent for Linear Systems: Polyak's Stepsize and Implicit Bias
by: Malitsky, Yura, et al.
Published: (2025)

A Busemann hybrid projection-proximal point algorithm for optimization problems on Hadamard manifolds
by: Millán, R. Díaz, et al.
Published: (2026)

Active set identification and rapid convergence for degenerate primal-dual problems
by: Díaz, Mateo, et al.
Published: (2026)

Fast Krasnoselskii-Mann Method with Overrelaxation and Preconditioners
by: Boţ, Radu I., et al.
Published: (2024)

A first-order method for nonconvex-nonconcave minimax problems under a local Kurdyka-Lojasiewicz condition
by: Lu, Zhaosong, et al.
Published: (2025)

A first-order augmented Lagrangian method for constrained minimax optimization
by: Lu, Zhaosong, et al.
Published: (2023)

First-order penalty methods for bilevel optimization
by: Lu, Zhaosong, et al.
Published: (2023)

Solving bilevel optimization via sequential minimax optimization
by: Lu, Zhaosong, et al.
Published: (2025)

Graph splitting methods: Fixed points and strong convergence for linear subspaces
by: Aragón-Artacho, Francisco J., et al.
Published: (2025)

A low-rank augmented Lagrangian method for large-scale semidefinite programming based on a hybrid convex-nonconvex approach
by: Monteiro, Renato D. C., et al.
Published: (2024)

Distributed accelerated proximal conjugate gradient methods for multi-agent constrained optimization problems
by: Gebrie, Anteneh Getachew
Published: (2023)

Stochastic Krasnoselskii-Mann Iterations: Convergence without Uniformly Bounded Variance
by: Cortild, Daniel, et al.
Published: (2026)

On the Convergence of HalpernSGD
by: Colao, Vittorio, et al.
Published: (2026)

Forward-backward algorithms devised by graphs
by: Aragón-Artacho, Francisco J., et al.
Published: (2024)

Nonlinear three-operator splitting algorithms with momentum for monotone inclusions
by: Qin, Liqian, et al.
Published: (2025)

New operator designs for Halpern iterations with explicit rates under Hölder error bounds
by: Barros, Pablo, et al.
Published: (2026)

A Theory of Composition and Duality of Extremal Optimal Fixed-Point Algorithms
by: Yoon, TaeHo, et al.
Published: (2026)

Bivariate rational approximations of the general temperature integral
by: Aghili, Alireza, et al.
Published: (2024)

A symmetric primal-dual algorithmic framework for saddle point problems
by: He, Hongjin, et al.
Published: (2022)

Krasnoselskii-Mann Iterations: Inertia, Perturbations and Approximation
by: Cortild, Daniel, et al.
Published: (2024)

On Opial's Lemma
by: Arakcheev, Aleksandr, et al.
Published: (2025)

Efficient parameter-free restarted accelerated gradient methods for convex and strongly convex optimization
by: Sujanani, Arnesh, et al.
Published: (2024)

The Chambolle-Pock method also converges weakly with $0 < θ\le 1$ and $τσ\|L\|^{2} < 4θ(2-θ)/(1 - 2θ+ 9θ^{2} - 4θ^{3})$
by: Upadhyaya, Manu
Published: (2026)