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This paper discusses the use of absolutely one-homogeneous regularization functionals in a variational, scale space, and inverse scale space setting to define a nonlinear spectral decomposition of input data. We present several theoretical…

Numerical Analysis · Computer Science 2016-01-13 Martin Burger , Guy Gilboa , Michael Moeller , Lina Eckardt , Daniel Cremers

In this work we investigate the computation of nonlinear eigenfunctions via the extinction profiles of gradient flows. We analyze a scheme that recursively subtracts such eigenfunctions from given data and show that this procedure yields a…

Numerical Analysis · Mathematics 2019-02-28 Leon Bungert , Martin Burger , Daniel Tenbrinck

These notes are meant as an introduction to the theory of nonlinear spectral theory. We will discuss the variational form of nonlninear eigenvalue problems and the corresponding non-linear Euler--Lagrange equations, as well as connections…

Spectral Theory · Mathematics 2025-06-11 Leon Bungert , Yury Korolev

In this work we develop a nonlinear decomposition, associated with nonlinear eigenfunctions of the p-Laplacian for p \in (1, 2). With this decomposition we can process signals of different degrees of smoothness. We first analyze solutions…

Analysis of PDEs · Mathematics 2019-09-18 Ido Cohen , Guy Gilboa

This paper discusses a generalization of spectral representations related to convex one-homogeneous regularization functionals, e.g. total variation or $\ell^1$-norms. Those functionals serve as a substitute for a Hilbert space structure…

Numerical Analysis · Mathematics 2015-03-19 Martin Burger , Lina Eckardt , Guy Gilboa , Michael Moeller

This work is concerned with the gradient flow of absolutely $p$-homogeneous convex functionals on a Hilbert space, which we show to exhibit finite ($p<2$) or infinite extinction time ($p \geq 2$). We give upper bounds for the finite…

Analysis of PDEs · Mathematics 2020-12-25 Leon Bungert , Martin Burger

This work is concerned with the convex analysis of functions defined on (not necessarily finite-dimensional) Hilbert spaces whose values depend solely on a certain ``spectrum'' of the arguments, a class we term ``spectral functions.'' We…

Optimization and Control · Mathematics 2026-03-11 Hòa T. Bùi , Minh N. Bùi , Christian Clason

The Eigendecomposition of quadratic forms (symmetric matrices) guaranteed by the spectral theorem is a foundational result in applied mathematics. Motivated by a shared structure found in inferential problems of recent interest---namely…

Machine Learning · Computer Science 2018-02-26 Mikhail Belkin , Luis Rademacher , James Voss

Nonlinear variational methods have become very powerful tools for many image processing tasks. Recently a new line of research has emerged, dealing with nonlinear eigenfunctions induced by convex functionals. This has provided new insights…

Computer Vision and Pattern Recognition · Computer Science 2016-09-28 Raz Z. Nossek , Guy Gilboa

We investigate a variational approach to nonpotential perturbations of gradient flows of nonconvex energies in Hilbert spaces. We prove existence of solutions to elliptic-in-time regularizations of gradient flows by combining the…

Analysis of PDEs · Mathematics 2016-05-04 Stefano Melchionna

Nonlinear eigenvalue problems for pairs of homogeneous convex functions are particular nonlinear constrained optimization problems that arise in a variety of settings, including graph mining, machine learning, and network science. By…

Optimization and Control · Mathematics 2022-09-15 Francesco Tudisco , Dong Zhang

Finding latent structures in data is drawing increasing attention in diverse fields such as image and signal processing, fluid dynamics, and machine learning. In this work we examine the problem of finding the main modes of gradient flows.…

Dynamical Systems · Mathematics 2020-12-29 Ido Cohen , Omri Azencot , Pavel Lifshitz , Guy Gilboa

Nonlinear spectral problems arise across a range of fields, including mechanical vibrations, fluid-solid interactions, and photonic crystals. Discretizing infinite-dimensional nonlinear spectral problems often introduces significant…

Numerical Analysis · Mathematics 2025-04-25 Matthew J. Colbrook , Catherine Drysdale

In this paper, we consider a convex function defined as a 1D-regularized total variation with nonhomogeneous coefficients, and prove the Main Theorem concerned with the decomposition of the subdifferential of this convex function to a…

Analysis of PDEs · Mathematics 2021-04-27 Shodai Kubota

We present in this paper the motivation and theory of nonlinear spectral representations, based on convex regularizing functionals. Some comparisons and analogies are drawn to the fields of signal processing, harmonic analysis and sparse…

Spectral Theory · Mathematics 2015-10-06 Guy Gilboa , Michael Moeller , Martin Burger

Spectral measures arise in numerous applications such as quantum mechanics, signal processing, resonances, and fluid stability. Similarly, spectral decompositions (pure point, absolutely continuous and singular continuous) often…

Spectral Theory · Mathematics 2021-03-02 Matthew John Colbrook

The nonlinear Schroedinger model is a prototypical dispersive wave equation that features finite time blowup, either for supercritical exponents (for fixed dimension) or for supercritical dimensions (for fixed nonlinearity exponent). Upon…

Pattern Formation and Solitons · Physics 2022-07-20 S. J. Chapman , M. E. Kavousanakis , E. G. Charalampidis , I. G. Kevrekidis , P. G. Kevrekidis

In this paper, we provide the spectral decomposition in Hilbert space of the $\mathcal{C}_0$-semigroup $P$ and its adjoint $\hatP$ having as generator, respectively, the Caputo and the right-sided Riemann-Liouville fractional derivatives of…

Probability · Mathematics 2019-05-28 Pierre Patie , Yixuan Zhao

The aim of this paper is to offer an original and comprehensive spectral theoretical approach to the study of convergence to equilibrium, and in particular of the hypocoercivity phenomenon, for contraction semigroups in Hilbert spaces. Our…

Probability · Mathematics 2022-03-08 Pierre Patie , Aditya Vaidyanathan

This paper is dedicated to the unique continuation properties of the solutions to nonlinear variational problems. Our analysis covers the case of nonlinear autonomous functionals depending on the gradient, as well as more general double…

Analysis of PDEs · Mathematics 2024-08-02 Lorenzo Ferreri , Luca Spolaor , Bozhidar Velichkov
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