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We consider the nonconvex minimization problem, with quartic objective function, that arises in the exact recovery of a configuration matrix $P\in \R^{nd}$ of $n$ points when a Euclidean distance matrix, \EDMp, is given with embedding…

Optimization and Control · Mathematics 2025-07-29 Mengmeng Song , Douglas Goncalves , Woosuk L. Jung , Carlile Lavor , Antonio Mucherino , Henry Wolkowicz

In this paper, we investigate the minimization of a functional in which the usual perimeter is competing with a nonlocal singular term comparable (but not necessarily equal to) a fractional perimeter. The motivation for this problem is a…

Analysis of PDEs · Mathematics 2020-09-09 Antoine Mellet , Yijing Wu

Non-convex optimization is ubiquitous in modern machine learning. Researchers devise non-convex objective functions and optimize them using off-the-shelf optimizers such as stochastic gradient descent and its variants, which leverage the…

Machine Learning · Computer Science 2021-03-26 Tengyu Ma

We study $H^1$ versus $C^1$ local minimizers for functionals defined on spaces of symmetric functions, namely functions that are invariant by the action of some subgroups of $\mathcal{O}(N)$. These functionals, in many cases, are associated…

Analysis of PDEs · Mathematics 2015-05-08 Leonelo Iturriaga , Ederson Moreira dos Santos , Pedro Ubilla

The paper is devoted to deriving novel second-order necessary and sufficient optimality conditions for local minimizers in rather general classes of nonsmooth unconstrained and constrained optimization problems in finite-dimensional spaces.…

Optimization and Control · Mathematics 2025-01-07 Pham Duy Khanh , Vu Vinh Huy Khoa , Boris S. Mordukhovich , Vo Thanh Phat

The simplex algorithm for linear programming is based on the fact that any local optimum with respect to the polyhedral neighborhood is also a global optimum. We show that a similar result carries over to submodular maximization. In…

Data Structures and Algorithms · Computer Science 2017-12-01 Simon Bruggmann , Rico Zenklusen

This paper investigates general and generalized differentiation properties of the optimal value function associated with perturbed optimization problems. Fundamental results on nearly convex sets and functions in infinite-dimensional spaces…

Optimization and Control · Mathematics 2025-10-24 V. S. T. Long , B. S. Mordukhovich , N. M. Nam , L. White

We study nonconvex homogeneous quadratically constrained quadratic optimization with one or two constraints, denoted by (QQ1) and (QQ2), respectively. (QQ2) contains (QQ1), trust region subproblem (TRS) and ellipsoid regularized total least…

Optimization and Control · Mathematics 2021-07-22 Mengmeng Song , Hongying Liu , Yong Xia

The problem of finding global minima of nonlinear discrete functions arises in many fields of practical matters. In recent years, methods based on discrete filled functions become popular as ways of solving these sort of problems. However,…

Optimization and Control · Mathematics 2020-03-26 Juan Di Mauro , Hugo D. Scolnik

In this paper, we introduce a new functional point of view on bilevel optimization problems for machine learning, where the inner objective is minimized over a function space. These types of problems are most often solved by using methods…

Machine Learning · Statistics 2024-12-10 Ieva Petrulionyte , Julien Mairal , Michael Arbel

Energy functionals describing phase transitions in crystalline solids are often non-quasiconvex and minimizers might therefore not exist. On the other hand, there might be infinitely many gradient Young measures, modelling microstructures,…

Analysis of PDEs · Mathematics 2018-11-21 Francesco Della Porta

Recently, a new local optimality concept for minimax problems, termed calm local minimax points, has been introduced. In this paper, we extend this concept to a general class of nonsmooth, nonconvex nonconcave minimax problems with coupled…

Optimization and Control · Mathematics 2025-10-07 Xiaoxiao Ma , Jane Ye

In this paper, we study the problem of optimizing a two-layer artificial neural network that best fits a training dataset. We look at this problem in the setting where the number of parameters is greater than the number of sampled points.…

Machine Learning · Computer Science 2017-11-01 Digvijay Boob , Guanghui Lan

In this paper, in terms of three types of generalized second-order derivatives of a nonsmooth function, we mainly study the corresponding second-order optimality conditions in a Hilbert space and prove the equivalence among these optimality…

Optimization and Control · Mathematics 2016-07-25 Zhou Wei , Jen-Chih Yao

Bilevel optimization problems embed the optimality of a subproblem as a constraint of another optimization problem. We introduce the concept of near-optimality robustness for bilevel optimization, protecting the upper-level solution…

Optimization and Control · Mathematics 2024-07-15 Mathieu Besançon , Miguel F. Anjos , Luce Brotcorne

We consider a small random perturbation of the energy functional $$ [u]^2_{H^s(\Lambda, R^d)} + \int_\Lambda W(u(x)) dx $$ for $s \in (0,1),$ where the non-local part $ [u]^2_{H^s(\Lambda,R^d)}$ denotes the total contribution from $\Lambda…

Mathematical Physics · Physics 2013-08-27 Nicolas Dir , Enza Orlandi

On the two dimensional sphere, we consider axisymmetric critical points of an isoperimetric problem perturbed by a long-range interaction term. When the parameter controlling the nonlocal term is sufficiently large, we prove the existence…

Classical Analysis and ODEs · Mathematics 2014-08-26 Rustum Choksi , Ihsan Topaloglu , Gantumur Tsogtgerel

Time analysis of oscillations of a particle between wells in the one-dimensional double-well potential with infinite high outside walls, based on wave packet use and energy spectrum analysis, is presented. For the double-well potential of…

Nuclear Theory · Physics 2007-05-23 Sergei P. Maydanyuk

We analyze the topological structure of the Nehari set for a class of functionals depending on a real parameter $\lambda$, and having two degrees of homogeneity. A special attention is paid to the extremal parameter $\lambda^*$, which is…

Analysis of PDEs · Mathematics 2022-03-07 Humberto Ramos Quoirin , Kaye Silva

Submodular continuous functions are a category of (generally) non-convex/non-concave functions with a wide spectrum of applications. We characterize these functions and demonstrate that they can be maximized efficiently with approximation…

Machine Learning · Computer Science 2019-05-07 Andrew An Bian , Baharan Mirzasoleiman , Joachim M. Buhmann , Andreas Krause