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In convex optimization, continuous-time counterparts have been a fruitful tool for analyzing momentum algorithms. Fewer such examples are available when the function to minimize is non-convex. In several cases, discrepancies arise between…

Optimization and Control · Mathematics 2026-01-07 Julien Hermant , Jean-François Aujol , Charles Dossal , Lorick Huang , Aude Rondepierre

A new optimization framework to design steady equilibrium solutions of the Vlasov-Poisson system by means of external electric fields is presented. This optimization framework requires the minimization of an ensemble functional with…

Optimization and Control · Mathematics 2024-07-24 Alfio Borzì , Gennaro Infante , Giovanni Mascali

The work deals with a study of a nonlinear parabolic equation with hysteresis, containing a nonlinear monotone operator in the diffusion term. The well-posedness of the model equation is addressed by using an implicit time discretization…

Analysis of PDEs · Mathematics 2020-05-07 Achille Landri Pokam Kakeu , Jean Louis Woukeng

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…

Optimization and Control · Mathematics 2024-04-24 Robert Ernö Csetnek , Mikhail A. Karapetyants

The path spaces of a directed graph play an important role in the study of graph $\css$. These are topological spaces that were originally constructed using groupoid and inverse semigroup techniques. In this paper, we develop a simple,…

Operator Algebras · Mathematics 2007-05-23 Alan L. T. Paterson , Amy E. Welch

In this paper, we study the three-dimensional non-isentropic compressible fluid-particle flows. The system involves coupling between the Vlasov-Fokker-Planck equation and the non-isentropic compressible Navier-Stokes equations through…

Analysis of PDEs · Mathematics 2019-04-18 Yanmin Mu , Dehua Wang

We consider Tikhonov regularization of control-constrained optimal control problems. We present new a-priori estimates for the regularization error assuming measure and source-measure conditions. In the special case of bang-bang solutions,…

Optimization and Control · Mathematics 2017-12-08 Nikolaus von Daniels

Machine Learning algorithms are typically regarded as appropriate optimization schemes for minimizing risk functions that are constructed on the training set, which conveys statistical flavor to the corresponding learning problem. When the…

Machine Learning · Computer Science 2019-07-05 Alessandro Betti , Marco Gori

We address the classical issue of appropriate choice of the regularization and discretization level for the Tikhonov regularization of an inverse problem with imperfectly measured data. We focus on the fact that the proper choice of the…

Numerical Analysis · Mathematics 2014-10-24 Vinicius Albani , Adriano De Cezaro , Jorge P. Zubelli

We review the concept of well-posedness in the context of evolutionary problems from mathematical physics for a particular subclass of problems from elasticity theory. The complexity of physical phenomena appears as encoded in so called…

Analysis of PDEs · Mathematics 2016-10-27 Rainer Picard , Sascha Trostorff , Marcus Waurick

An optimal control problem in the space of Borel measures governed by the Poisson equation is investigated. The characteristic feature of the problem under consideration is the Tikhonov regularization term in form of the transportation…

Optimization and Control · Mathematics 2025-06-04 Christian Meyer , Gerd Wachsmuth

In this paper we address the problem of well-posedness of multi-dimensional topological Euler-alignment models introduced in \cite{ST-topo}. The main result demonstrates local existence and uniqueness of classical solutions in class…

Analysis of PDEs · Mathematics 2019-10-04 David N. Reynolds , Roman Shvydkoy

This paper studies the well-posedness of a class of nonlocal parabolic partial differential equations (PDEs), or equivalently equilibrium Hamilton-Jacobi-Bellman equations, which has a strong tie with the characterization of the equilibrium…

Analysis of PDEs · Mathematics 2026-05-12 Qian Lei , Chi Seng Pun

We review $H^{1}$-well-posedness for initial value problems of ordinary differential equations with state-dependent right-hand side. We streamline known approaches to infer existence and uniqueness of solutions for small times given a…

Classical Analysis and ODEs · Mathematics 2024-10-29 Bernhard Aigner , Marcus Waurick

As a main step in the numerical solution of control problems in continuous time, the controlled process is approximated by sequences of controlled Markov chains, thus discretising time and space. A new feature in this context is to allow…

Optimization and Control · Mathematics 2007-05-23 Markus Fischer , Markus Reiss

We establish, in a rather general setting, an analogue of DiPerna-Lions theory on well-posedness of flows of ODE's associated to Sobolev vector fields. Key results are a well-posedness result for the continuity equation associated to…

Functional Analysis · Mathematics 2014-12-02 Luigi Ambrosio , Dario Trevisan

Recently, many machine learning optimizers have been analysed considering them as the asymptotic limit of some differential equations when the step size goes to zero. In other words, the optimizers can be seen as a finite difference scheme…

Numerical Analysis · Mathematics 2024-07-02 Bilel Bensaid , Gaël Poëtte , Rodolphe Turpault

The subject of this article is the introduction of a new concept of well-posedness of Bayesian inverse problems. The conventional concept of (Lipschitz, Hellinger) well-posedness in [Stuart 2010, Acta Numerica 19, pp. 451-559] is difficult…

Statistics Theory · Mathematics 2020-03-16 Jonas Latz

We generalize the concept "well-posed linear system" to stochastic linear control systems and study some basic properties of such kind systems. Under our generalized definition, we show the well-posedness of the stochastic heat equation and…

Optimization and Control · Mathematics 2015-07-07 Qi Lu

Herein, a methodology is developed to replicate functions, measures and stochastic processes onto a compact metric space. Many results are easily established for the replica objects and then transferred back to the original ones. Two…

Probability · Mathematics 2020-11-03 Chi Dong , Michael A. Kouritzin
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