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Hessian operators arising in inverse problems governed by partial differential equations (PDEs) play a critical role in delivering efficient, dimension-independent convergence for both Newton solution of deterministic inverse problems, as…

The top-k operator returns a sparse vector, where the non-zero values correspond to the k largest values of the input. Unfortunately, because it is a discontinuous function, it is difficult to incorporate in neural networks trained…

Machine Learning · Computer Science 2023-06-06 Michael E. Sander , Joan Puigcerver , Josip Djolonga , Gabriel Peyré , Mathieu Blondel

There are numerous studies focusing on the convergence of the principal eigenvalue $\lambda(s)$ as $s\to+\infty$ corresponding to the elliptic eigenvalue problem \begin{align*}…

Analysis of PDEs · Mathematics 2023-11-14 Xueli Bai , Xin Xu , Kexin Zhang , Maolin Zhou

This work deals with theoretical and numerical aspects related to the behavior of the Steklov-Lam\'e eigenvalues on variable domains. After establishing the eigenstructure for the disk, we prove that for a certain class of Lam\'e…

Optimization and Control · Mathematics 2022-05-24 Beniamin Bogosel , Pedro R. S. Antunes

In this paper we present an elementary theory about the existence of eigenvalues for fully nonlinear radially symmetric 1-homogeneous operators. A general theory for first eigenvalues and eigenfunctions of 1-homogeneous fully nonlinear…

Analysis of PDEs · Mathematics 2009-08-10 Maria J. Esteban , Patricio Felmer , Alexander Quaas

The paper is concerned with the principal eigenvalue of some linear elliptic operators with drift in two dimensional space. We provide a refined description of the asymptotic behavior for the principal eigenvalue as the drift rate…

Analysis of PDEs · Mathematics 2024-05-17 Shuang Liu , Yuan Lou , Maolin Zhou

We study the optimization of (strongly) quasar-convex functions, a class that arises naturally in many machine learning and data science applications due to its favorable properties. The fundamental properties of this class are first…

Optimization and Control · Mathematics 2026-04-30 Masoud Ahookhosh , Jose M. M. de Brito , Alireza Kabgani , Felipe Lara , Jinyun Yuan

The convex hull property is the natural generalization of maximum principles from scalar to vector valued functions. Maximum principles for finite element approximations are often crucial for the preservation of qualitative properties of…

Numerical Analysis · Mathematics 2019-05-22 Lars Diening , Christian Kreuzer , Sebastian Schwarzacher

In our previous paper on this topic, we introduced the notion of k-Hessian measure associated with a continuous k-convex function in a domain \Om in Euclidean n-space, k=1,...,n, and proved a weak continuity result with respect to local…

Functional Analysis · Mathematics 2007-05-23 Neil S. Trudinger , Xu-Jia Wang

In this paper we investigate a class of $2$-Hessian equations and establish a minimum principle for a $P$-function in the sense of L.E. Payne (see R. Sperb \cite{Sp81}). The analysis is based on a sharp matrix inequality providing an…

Analysis of PDEs · Mathematics 2026-03-23 Cristian Enache

This paper considers the problem of approximating the inverse of the wave-equation Hessian, also called normal operator, in seismology and other types of wave-based imaging. An expansion scheme for the pseudodifferential symbol of the…

Numerical Analysis · Mathematics 2015-03-17 Laurent Demanet , Pierre-David Létourneau , Nicolas Boumal , Henri Calandra , Jiawei Chiu , Stanley Snelson

Spectral analysis of convex processes has led to many results in the analysis of differential inclusions with a convex process. In particular the characterization of eigenvalues with eigenvectors in a given cone has led to results on…

Optimization and Control · Mathematics 2022-03-31 Jaap Eising , M. Kanat Camlibel

Given a Hilbert space $\mathcal H$ and a finite measure space $\Omega$, the approximation of a vector-valued function $f: \Omega \to \mathcal H$ by a $k$-dimensional subspace $\mathcal U \subset \mathcal H$ plays an important role in…

Numerical Analysis · Mathematics 2024-08-07 Daniel Kressner , Tingting Ni , André Uschmajew

In this paper we solve a problem raised by Guti\'errez and Montanari about comparison principles for $H-$convex functions on subdomains of Heisenberg groups. Our approach is based on the notion of the sub-Riemannian horizontal normal…

Analysis of PDEs · Mathematics 2016-02-15 Zoltán M. Balogh , Andrea Calogero , Alexandru Kristály

This paper is concerned with the hard thresholding operator which sets all but the $k$ largest absolute elements of a vector to zero. We establish a {\em tight} bound to quantitatively characterize the deviation of the thresholded solution…

Machine Learning · Statistics 2020-08-12 Jie Shen , Ping Li

Estimation of convex functions finds broad applications in engineering and science, while convex shape constraint gives rise to numerous challenges in asymptotic performance analysis. This paper is devoted to minimax optimal estimation of…

Statistics Theory · Mathematics 2013-06-11 Teresa M. Lebair , Jinglai Shen , Xiao Wang

We establish Maximum Principles which apply to vectorial approximate minimizers of the general integral functional of Calculus of Variations. Our main result is a version of the Convex Hull Property. The primary advance compared to results…

Analysis of PDEs · Mathematics 2013-04-22 Nikolaos I. Katzourakis

We have optimized the zero frequency first hyperpolarizability \beta of a one-dimensional piecewise linear potential well containing a single electron by adjusting the shape of that potential. With increasing numbers of parameters in the…

Chemical Physics · Physics 2015-03-17 T. J. Atherton , J. Lesnefsky , G. A. Wiggers , R. G. Petschek

Tougeron's implicit function theorem and Hensel's lemma are well known representatives concerning 2k-approximation/k-nondegeneracy implying existence of solutions with identity of order k. This note aims to extend this principle to…

Algebraic Geometry · Mathematics 2020-06-17 Matthias Stiefenhofer

In tensor eigenvalue problems, one is likely to be more interested in H-eigenvalues of tensors. The largest H-eigenvalue of a nonnegative tensor or of a uniform hypergraph is the spectral radius of the tensor or of the uniform hypergraph.…

Numerical Analysis · Mathematics 2023-06-27 Hongying Lin , Lu Zheng , Bo Zhou
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