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This paper proposes a new algorithm for solving constrained global optimization problems where both the objective function and constraints are one-dimensional non-differentiable multiextremal Lipschitz functions. Multiextremal constraints…

Optimization and Control · Mathematics 2011-07-27 Yaroslav D. Sergeyev

The performance of optimization methods is often tied to the spectrum of the objective Hessian. Yet, conventional assumptions, such as smoothness, do often not enable us to make finely-grained convergence statements -- particularly not for…

Optimization and Control · Mathematics 2024-02-08 Nikita Doikov , Sebastian U. Stich , Martin Jaggi

We consider the minimization of submodular functions subject to ordering constraints. We show that this optimization problem can be cast as a convex optimization problem on a space of uni-dimensional measures, with ordering constraints…

Machine Learning · Computer Science 2017-07-31 Francis Bach

In this paper, we consider a class of structured nonconvex nonsmooth optimization problems, in which the objective function is formed by the sum of a possibly nonsmooth nonconvex function and a differentiable function whose gradient is…

Optimization and Control · Mathematics 2024-10-01 Tan Nhat Pham , Minh N. Dao , Rakibuzzaman Shah , Nargiz Sultanova , Guoyin Li , Syed Islam

In this paper, we consider a broad class of nonsmooth and nonconvex fractional programs, where the numerator can be written as the sum of a continuously differentiable convex function whose gradient is Lipschitz continuous and a proper…

Optimization and Control · Mathematics 2022-01-19 Radu Ioan Boţ , Minh N. Dao , Guoyin Li

We study the problem of nonparametric estimation of the fractional derivative of unknown distribution function and of spectral function and show that these problems are well posed when the order of derivative is less than 0.5. We prove also…

Statistics Theory · Mathematics 2014-12-23 E. Ostrovsky , L. Sirota

This paper presents a unified analysis for the proximal subgradient method (Prox-SubGrad) type approach to minimize an overall objective of $f(x)+r(x)$, subject to convex constraints, where both $f$ and $r$ are weakly convex, nonsmooth, and…

Optimization and Control · Mathematics 2026-01-23 Daoli Zhu , Lei Zhao , Shuzhong Zhang

We give sufficient conditions on the exponent $p: \mathbb R^d\rightarrow [1,\infty)$ for the boundedness of the non-centered Gaussian maximal function on variable Lebesgue spaces $L^{p(\cdot)}(\mathbb R^d, \gamma_d)$, as well as of the new…

Analysis of PDEs · Mathematics 2024-12-12 Estefanía Dalmasso , Roberto Scotto

In this work, we use the integral definition of the fractional Laplace operator and study a sparse optimal control problem involving a fractional, semilinear, and elliptic partial differential equation as state equation; control constraints…

Optimization and Control · Mathematics 2023-12-14 Francisco Bersetche , Francisco Fuica , Enrique Otarola , Daniel Quero

We obtain some new characterizations of a variable version of Lipschitz spaces in terms of the boundedness of commutators of sharp maximal functions, fractional maximal functions or fractional maximal commutators in the context of the…

Functional Analysis · Mathematics 2022-11-17 Xuechun Yang , Zhenzhen Yang , Baode Li

This paper continues the investigations from [7] and is concerned with the derivation of first-order conditions for a control constrained optimization problem governed by a non-smooth elliptic PDE. The control enters the state equation not…

Optimization and Control · Mathematics 2025-02-11 Livia Betz

We focus on finding sparse and least-$\ell_1$-norm solutions for unconstrained nonlinear optimal control problems. Such optimization problems are non-convex and non-smooth, nevertheless recent versions of Newton method for under-determined…

Optimization and Control · Mathematics 2019-08-28 Boris Polyak , Andrey Tremba

In this paper we study optimal control problems in Wasserstein spaces, which are suitable to describe macroscopic dynamics of multi-particle systems. The dynamics is described by a parametrized continuity equation, in which the Eulerian…

Optimization and Control · Mathematics 2019-08-30 Giulia Cavagnari , Antonio Marigonda , Benedetto Piccoli

The paper studies integral functionals with non-smooth functions from L_2 defined on solutions of ODEs. Some regularity is obtained in the form of estimates of L_2-norm for these functionals. This result is used for regularization of…

Optimization and Control · Mathematics 2010-11-01 Nikolai Dokuchaev

The aim of this paper is to establish well-posedness properties for hyperbolic PDEs on Fourier Lebesgue spaces. We consider hyperbolic operators with complex characteristics. Since our approach comes from harmonic analysis, we establish…

Analysis of PDEs · Mathematics 2026-02-02 Duván Cardona , William Obeng-Denteh , Frederick Opoku

Sparse optimization seeks an optimal solution with few nonzero entries. To achieve this, it is common to add to the criterion a penalty term proportional to the $\ell_1$-norm, which is recognized as the archetype of sparsity-inducing norms.…

Optimization and Control · Mathematics 2026-03-05 Jean-Philippe Chancelier , Michel de Lara , Antoine Deza , Lionel Pournin

We investigate a distributed optimal control problem for the viscous Camassa--Holm equations with sparse controls and a general cost functional. Considering three different forms of sparsity-promoting terms, we prove the existence of…

Optimization and Control · Mathematics 2026-04-06 Giang Nguyen Hai Ha

We adopt the integral definition of the fractional Laplace operator and study an optimal control problem on Lipschitz domains that involves a fractional elliptic partial differential equation (PDE) as state equation and a control variable…

Numerical Analysis · Mathematics 2024-02-14 Francisco Bersetche , Francisco Fuica , Enrique Otarola , Daniel Quero

This paper develops a novel approach to necessary optimality conditions for constrained variational problems defined in generally incomplete subspaces of absolutely continuous functions. Our approach involves reducing a variational problem…

Optimization and Control · Mathematics 2021-11-01 Ashkan Mohammadi , Boris Mordukhovich

We present a new method for minimizing the sum of a differentiable convex function and an $\ell_1$-norm regularizer. The main features of the new method include: $(i)$ an evolving set of indices corresponding to variables that are predicted…

Optimization and Control · Mathematics 2016-02-24 Tianyi Chen , Frank E. Curtis , Daniel P. Robinson
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