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This is the first of several monographs to be devoted to the optics of accelerated systems. They are being published for the benefit of those who may wish to have another way of looking at kineoptical problems, and also to demonstrate that…

Optics · Physics 2007-05-23 A. I. A. Adewole

Nonconservative evolution problems describe irreversible processes and dissipative effects in a broad variety of phenomena. Such problems are often characterised by a conservative part, which can be modelled as a Hamiltonian term, and a…

Numerical Analysis · Mathematics 2025-05-12 Damiano Lombardi , Cecilia Pagliantini

Following Demidovich's concept and definition of convergent systems, we analyze the optimal nonlinear damping control, recently proposed [1] for the second-order systems. Targeting the problem of output regulation, correspondingly tracking…

Systems and Control · Electrical Eng. & Systems 2021-06-03 Michael Ruderman

This is a handbook of simple proofs of the convergence of gradient and stochastic gradient descent type methods. We consider functions that are Lipschitz, smooth, convex, strongly convex, and/or Polyak-{\L}ojasiewicz functions. Our focus is…

Optimization and Control · Mathematics 2024-03-12 Guillaume Garrigos , Robert M. Gower

The purpose of this manuscript is to review my recent activity on three main research topics. The first concerns the nature of low temperature amorphous solids and their relation with the spin glass transition in a magnetic field. This is…

Disordered Systems and Neural Networks · Physics 2024-05-13 Pierfrancesco Urbani

Due to its applications in many different places in machine learning and other connected engineering applications, the problem of minimization of a smooth function that satisfies the Polyak-{\L}ojasiewicz condition receives much attention…

Optimization and Control · Mathematics 2022-12-09 Ilya A. Kuruzov , Fedor S. Stonyakin , Mohammad S. Alkousa

We provide a comprehensive study of the convergence of the forward-backward algorithm under suitable geometric conditions, such as conditioning or {\L}ojasiewicz properties. These geometrical notions are usually local by nature, and may…

Optimization and Control · Mathematics 2023-12-25 Guillaume Garrigos , Lorenzo Rosasco , Silvia Villa

Treating optimization methods as dynamical systems can be traced back centuries ago in order to comprehend the notions and behaviors of optimization methods. Lately, this mind set has become the driving force to design new optimization…

Optimization and Control · Mathematics 2019-09-24 Arman Sharifi Kolarijani , Peyman Mohajerin Esfahani , Tamás Keviczky

We propose to use the {\L}ojasiewicz inequality as a general tool for analyzing the convergence rate of gradient descent on a Hilbert manifold, without resorting to the continuous gradient flow. Using this tool, we show that a Sobolev…

Numerical Analysis · Mathematics 2021-05-21 Ziyun Zhang

The aim of this work is to study the geometry underlying mechanics and its application to describe autonomous and nonautonomous conservative dynamical systems of different types; as well as dissipative dynamical systems. We use different…

Mathematical Physics · Physics 2025-05-07 Miguel C. Muñoz-Lecanda , Narciso Román-Roy

We consider a model for an incompressible visoelastic fluid. It consists of the Navier-Stokes equations involving an elastic term in the stress tensor and a transport equation for the evolution of the deformation gradient. The novel feature…

Analysis of PDEs · Mathematics 2019-10-23 Martin Kalousek

Our work is part of the close link between continuous-time dissipative dynamical systems and optimization algorithms, and more precisely here, in the stochastic setting. We aim to study stochastic convex minimization problems through the…

Optimization and Control · Mathematics 2025-02-21 Rodrigo Maulen-Soto , Jalal Fadili , Hedy Attouch , Peter Ochs

There are much recent interests in solving noncovnex min-max optimization problems due to its broad applications in many areas including machine learning, networked resource allocations, and distributed optimization. Perhaps, the most…

Optimization and Control · Mathematics 2021-12-20 Thinh T. Doan

In 1963, Polyak proposed a simple condition that is sufficient to show a global linear convergence rate for gradient descent. This condition is a special case of the \L{}ojasiewicz inequality proposed in the same year, and it does not…

Machine Learning · Computer Science 2020-09-15 Hamed Karimi , Julie Nutini , Mark Schmidt

In this letter we study the proximal gradient dynamics. This recently-proposed continuous-time dynamics solves optimization problems whose cost functions are separable into a nonsmooth convex and a smooth component. First, we show that the…

Optimization and Control · Mathematics 2024-11-22 Anand Gokhale , Alexander Davydov , Francesco Bullo

This paper is devoted to the variational inequality problems. We consider two classes of problems, the first is classical constrained variational inequality and the second is the same problem with functional (inequality type) constraints.…

Optimization and Control · Mathematics 2025-06-04 Mohammad S. Alkousa , Belal A. Alashqar , Fedor S. Stonyakin , Tarek Nabhani , Seydamet S. Ablaev

We consider the asymptotic behavior of the soltion to the wave equation with time-dependent damping and analytic nonlinearity. Our main goal is to prove the convergence of a global solution to an equilibrium as time goes to infinity by…

Analysis of PDEs · Mathematics 2013-09-11 Zhe Jiao

The present book is the first publication in English considered the modern problems of control theory and analysis connected with a concept of system zeros. The previous book by Ye.M. Smagina (1990) had been written in Russian and it is…

Dynamical Systems · Mathematics 2007-05-23 Ye. M. Smagina

For a model convection-diffusion problem, we address the presence of oscillatory discrete solutions, and study difficulties in recovering standard approximation results for its solution. We justify the presence of non-physical oscillations…

Numerical Analysis · Mathematics 2026-01-15 Constantin Bacuta

In a Hilbert setting, for convex differentiable optimization, we develop a general framework for adaptive accelerated gradient methods. They are based on damped inertial dynamics where the coefficients are designed in a closed-loop way.…

Optimization and Control · Mathematics 2025-01-28 Hedy Attouch , Radu Ioan Bot , Dang-Khoa Nguyen
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