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Composite minimization involves a collection of functions which are aggregated in a nonsmooth manner. It covers, as a particular case, smooth approximation of minimax games, minimization of max-type functions, and simple composite…

Optimization and Control · Mathematics 2025-03-04 Yassine Nabou , Ion Necoara

In this paper, nonconvex and nonsmooth models for compressed sensing (CS) and low rank matrix completion (MC) is studied. The problem is formulated as a nonconvex regularized leat square optimization problems, in which the l0-norm and the…

Optimization and Control · Mathematics 2016-05-03 Zhuo-Xu Cui , Qibin Fan

Motivated by recent increased interest in optimization algorithms for non-convex optimization in application to training deep neural networks and other optimization problems in data analysis, we give an overview of recent theoretical…

In this note, we announce new regularity results for some locally integrable distributional solutions to Poisson's equation. This includes, for example, the standard solutions obtained by convolution with the fundamental solution. In…

Analysis of PDEs · Mathematics 2022-06-29 Rahul Garg , Daniel Spector

We investigate the stability with respect to homogenization of classes of integrals arising in the control-theoretic interpretation of some Hamilton-Jacobi equations. The prototypical case is the homogenization of energies with a Lagrangian…

Analysis of PDEs · Mathematics 2024-11-13 Andrea Braides , Gianni Dal Maso , Claude Le Bris

Self-consistent Hamiltonian formulation of scalar theory on the null plane is constructed following Dirac method. The theory contains also {\it constraint equations}. They would give, if solved, to a nonlinear and nonlocal Hamiltonian. The…

High Energy Physics - Theory · Physics 2010-11-01 Prem P. Srivastava

While there already exist randomized subspace Newton methods that restrict the search direction to a random subspace for a convex function, we propose a randomized subspace regularized Newton method for a non-convex function {and more…

Optimization and Control · Mathematics 2025-09-23 Terunari Fuji , Pierre-Louis Poirion , Akiko Takeda

The paper introduces and characterizes new notions of Lipschitzian and H\"olderian full stability of solutions to general parametric variational systems described via partial subdifferential and normal cone mappings acting in Hilbert…

Optimization and Control · Mathematics 2014-09-09 B. S. Mordukhovich , T. T. A. Nghia

Stability is a key property of both forward models and inverse problems, and depends on the norms considered in the relevant function spaces. For instance, stability estimates for hyperbolic partial differential equations are often based on…

Analysis of PDEs · Mathematics 2026-04-13 Rima Alaifari , Giovanni S. Alberti , Tandri Gauksson

We perform the Hamiltonian analysis for the lowest-order effective action, up to second order in derivatives, of the complete Horava theory. The model includes the invariant terms that depend on \partial_i ln N proposed by Blas, Pujolas and…

High Energy Physics - Theory · Physics 2011-12-08 Jorge Bellorín , Alvaro Restuccia

We address combinatorial problems that can be formulated as minimization of a partially separable function of discrete variables (energy minimization in graphical models, weighted constraint satisfaction, pseudo-Boolean optimization, 0-1…

Computer Vision and Pattern Recognition · Computer Science 2015-05-05 Alexander Shekhovtsov

Much research has been devoted to the problem of restoring Poissonian images, namely for medical and astronomical applications. However, the restoration of these images using state-of-the-art regularizers (such as those based on multiscale…

Optimization and Control · Mathematics 2012-10-10 Mário A. T. Figueiredo , José M. Bioucas-Dias

Although the \emph{residual method}, or \emph{constrained regularization}, is frequently used in applications, a detailed study of its properties is still missing. This sharply contrasts the progress of the theory of Tikhonov…

Optimization and Control · Mathematics 2012-12-06 Markus Grasmair , Markus Haltmeier , Otmar Scherzer

In this work we use variational methods to prove results on existence and concentration of solutions to a problem in $\mathbb{R}^N$ involving the $1-$Laplacian operator. A thorough analysis on the energy functional defined in the space of…

Analysis of PDEs · Mathematics 2017-02-23 C. O. Alves , M. T. O. Pimenta

We obtain regularity conditions of a new type of problems of the calculus of variations with second-order derivatives. As a corollary, we get non-occurrence of the Lavrentiev phenomenon. Our main result asserts that autonomous integral…

Optimization and Control · Mathematics 2008-02-23 Moulay Rchid Sidi Ammi , Delfim F. M. Torres

The goal of this paper is to settle the study of non-commutative optimal transport problems with convex regularization, in their static and finite-dimensional formulations. We consider both the balanced and unbalanced problem and show in…

Mathematical Physics · Physics 2025-06-27 Emanuele Caputo , Augusto Gerolin , Nataliia Monina , Lorenzo Portinale

The simplest toroidally compactified string theories exhibit a duality between large and small radii: compactification on a circle, for example, is invariant under R goes to 1/R. Compactification on more general Lorentzian lattices (i.e.…

High Energy Physics - Theory · Physics 2010-11-01 Eva Silverstein

We study the existence of $L^2$ normalized solutions for nonlinear Schr\"odinger equations and systems. Under new Palais-Smale type conditions we develop new deformation arguments for the constraint functional on $S_m=\{ u; \,…

Analysis of PDEs · Mathematics 2023-12-18 Norihisa Ikoma , Kazunaga Tanaka

This paper investigates the theoretical guarantees of L1-analysis regularization when solving linear inverse problems. Most of previous works in the literature have mainly focused on the sparse synthesis prior where the sparsity is measured…

Information Theory · Computer Science 2012-10-03 Samuel Vaiter , Gabriel Peyré , Charles Dossal , Jalal Fadili

We study stochastic second-order methods for solving general non-convex optimization problems. We propose using a special version of momentum to stabilize the stochastic gradient and Hessian estimates in Newton's method. We show that…

Optimization and Control · Mathematics 2025-06-27 El Mahdi Chayti , Nikita Doikov , Martin Jaggi
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