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In a real Hilbert space, we consider two classical problems: the global minimization of a smooth and convex function $f$ (i.e., a convex optimization problem) and finding the zeros of a monotone and continuous operator $V$ (i.e., a monotone…

Optimization and Control · Mathematics 2025-04-23 Hedy Attouch , Radu Ioan Bot , David Alexander Hulett , Dang-Khoa Nguyen

In this thesis we introduce the concept of a guided dynamical system, and exploit this idea to solve various problems in functional equations and PDE's. Our main results are 1) a necessary and sufficient condition for unique-solvability of…

Dynamical Systems · Mathematics 2007-05-23 Orr Shalit

A Tikhonov regularized inertial primal\mbox{-}dual dynamical system with time scaling and vanishing damping is proposed for solving a linearly constrained convex optimization problem in Hilbert spaces. The system under consideration…

Optimization and Control · Mathematics 2024-04-24 Ting-Ting Zhu , Rong Hu , Ya-Ping Fang

We devise and analyze hybrid polyhedral methods of arbitrary order for the approximation of div-curl systems on three-dimensional domains featuring non-trivial topology. The div-curl systems we are interested in stem from magnetostatics,…

Numerical Analysis · Mathematics 2025-06-25 Jérémy Dalphin , Jean-Pierre Ducreux , Simon Lemaire , Silvano Pitassi

We propose in this paper a proximal and contraction method for solving a convex mixed variational inequality problem in a real Hilbert space. To accelerate the convergence of our proposed method, we incorporate an inertial extrapolation…

Optimization and Control · Mathematics 2025-11-25 Chidi Elijah Nwakpa , Austine Efut Ofem , Kalu Okam Okorie , Chinedu Izuchukwu , Chibueze Christian Okeke

This work investigates a dynamical system functioning as a nonsmooth adaptation of the continuous Newton method, aimed at minimizing the sum of a primal lower-regular and a locally Lipschitz function, both potentially nonsmooth. The…

Optimization and Control · Mathematics 2024-12-10 Juan Guillermo Garrido , Pedro Pérez-Aros , Emilio Vilches

We present a general technique for the analysis of first-order methods. The technique relies on the construction of a duality gap for an appropriate approximation of the objective function, where the function approximation improves as the…

Optimization and Control · Mathematics 2019-12-12 Jelena Diakonikolas , Lorenzo Orecchia

We propose a comprehensive framework for solving constrained variational inequalities via various classes of evolution equations displaying multi-scale aspects. In an infinite-dimensional Hilbertian framework, the class of dynamical systems…

Optimization and Control · Mathematics 2025-07-25 Siqi Qu , Mathias Staudigl , Juan Peypouquet

In this study, we present a simulation-based numerical method for solving a class of singularly perturbed second-order differential equations that come from a simplified biologically motivated model of human gait. Important physical factors…

Numerical Analysis · Mathematics 2025-09-01 Shubhangini Gupta , Sourav Banerjee , Tamal Pramanick

We investigate a generalized Lagrange multiplier system in a Banach space, called a mixed variational-hemivariational inequality (MVHVI, for short), which contains a hemivariational inequality and a variational inequality. First, we employ…

Functional Analysis · Mathematics 2019-03-18 Yunru Bai , Stanislaw Migorski , Shengda Zeng

We incorporate inertial terms in the hybrid proximal-extragradient algorithm and investigate the convergence properties of the resulting iterative scheme designed for finding the zeros of a maximally monotone operator in real Hilbert…

Functional Analysis · Mathematics 2014-07-02 Radu Ioan Bot , Ernö Robert Csetnek

In this paper we study a second order dynamical system with variable coefficients in connection to the minimization problem of a smooth nonconvex function. The convergence of the trajectories generated by the dynamical system to a critical…

Optimization and Control · Mathematics 2025-10-21 Szilárd Csaba László

In this paper, we propose a general algorithmic framework for first-order methods in optimization in a broad sense, including minimization problems, saddle-point problems, and variational inequalities. This framework allows obtaining many…

In this paper, we propose a general extra-gradient scheme for solving monotone variational inequalities (VI), referred to here as Approximation-based Regularized Extra-gradient method (ARE). The first step of ARE solves a VI subproblem with…

Optimization and Control · Mathematics 2022-10-11 Kevin Huang , Shuzhong Zhang

We give an introduction into diffraction theory for aperiodic order. We focus on an approach via dynamical systems and the phenomenon of pure point diffraction. We review recent results and sketch proofs. We then present a new uniform…

Dynamical Systems · Mathematics 2007-12-11 Daniel Lenz

We focus on the linear convergence of generalized proximal point algorithms for solving monotone inclusion problems. Under the assumption that the associated monotone operator is metrically subregular or that the inverse of the monotone…

Optimization and Control · Mathematics 2022-03-29 Hui Ouyang

We establish, for smooth enough initial data, the global well-posedness (existence, uniqueness and continuous dependence on initial data) of solutions, for an inviscid three-dimensional {\it slow limiting ocean dynamics} model. This model…

Analysis of PDEs · Mathematics 2013-11-26 Chongsheng Cao , Aseel Farhat , Edriss S. Titi

We deal with monotone inclusion problems of the form $0\in Ax+Dx+N_C(x)$ in real Hilbert spaces, where $A$ is a maximally monotone operator, $D$ a cocoercive operator and $C$ the nonempty set of zeros of another cocoercive operator. We…

Functional Analysis · Mathematics 2013-06-04 Radu Ioan Bot , Ernö Robert Csetnek

In a Hilbert space setting H, for convex optimization, we analyze the fast convergence properties as t tends to infinity of the trajectories generated by a third-order in time evolution system. The function f to minimize is supposed to be…

Optimization and Control · Mathematics 2020-07-08 Hedy Attouch , Zaki Chbani , Hassan Riahi

First order optimization algorithms play a major role in large scale machine learning. A new class of methods, called adaptive algorithms, were recently introduced to adjust iteratively the learning rate for each coordinate. Despite great…

Machine Learning · Computer Science 2019-10-01 André Belotto da Silva , Maxime Gazeau