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The operator monotone functions defined in the positive half-line are of particular importance. We give a version of the theory in which integral representations for these functions can be established directly without invoking L\"owner's…

Operator Algebras · Mathematics 2014-03-18 Frank Hansen

The main focus of this paper is to study multi-valued linear monotone operators in the contexts of locally convex spaces via the use of their Fitzpatrick and Penot functions. Notions such as maximal monotonicity, uniqueness,…

Functional Analysis · Mathematics 2008-10-01 M. D. Voisei , C. Zalinescu

Maximally monotone operators play a key role in modern optimization and variational analysis. Two useful subclasses are rectangular (also known as star monotone) and paramonotone operators, which were introduced by Brezis and Haraux, and by…

Functional Analysis · Mathematics 2012-01-23 Heinz H. Bauschke , Xianfu Wang , Liangjin Yao

A generalization with singular weights of Moore-Penrose generalized inverses of closed range operators in Hilbert spaces is studied using the notion of compatibility of subspaces and positive operators.

Functional Analysis · Mathematics 2007-05-23 Gustavo Corach , Alejandra Maestripieri

The aim of this work is to characterize linear maps of inner pro\-duct infinite-dimensional vector spaces where the Moore-Penrose inverse exists. This MP inverse generalizes the well-known Moore-Penrose inverse of a matrix $A\in…

Rings and Algebras · Mathematics 2020-07-07 V. Cabezas Sánchez , F. Pablos Romo

Monotone operators and (firmly) nonexpansive mappings are fundamental objects in modern analysis and computational optimization. Five years ago, it was shown that if finitely many firmly nonexpansive mappings have or "almost have" fixed…

Functional Analysis · Mathematics 2018-09-06 Heinz H. Bauschke , Walaa M. Moursi

We prove that the principal pivot transform (also known as the partial inverse, sweep operator, or exchange operator in various contexts) maps matrices with positive imaginary part to matrices with positive imaginary part. We show that the…

Functional Analysis · Mathematics 2021-08-16 J. E. Pascoe , Ryan Tully-Doyle

Maximally monotone operators play important roles in optimization, variational analysis and differential equations. Finding zeros of maximally monotone operators has been a central topic. In a Hilbert space, we show that most resolvents are…

Optimization and Control · Mathematics 2013-01-29 Xianfu Wang

This paper considers the inversion of ill-posed linear operators. To regularise the problem the solution is enforced to lie in a non-convex subset. Theoretical properties for the stable inversion are derived and an iterative algorithm akin…

Numerical Analysis · Mathematics 2009-11-30 Thomas Blumensath

We develop a monotone, two-scale discretization for a class of integrodifferential operators of order $2s$, $s \in (0,1)$. We apply it to develop numerical schemes, and derive pointwise convergence rates, for linear and obstacle problems…

Numerical Analysis · Mathematics 2024-07-30 Juan Pablo Borthagaray , Ricardo H. Nochetto , Abner J. Salgado , Céline Torres

The correspondence between the class of nonexpansive mappings and the class of maximally monotone operators via the reflected resolvents of the latter has played an instrumental role in the convergence analysis of the splitting methods.…

Optimization and Control · Mathematics 2022-05-19 Leon Liu , Walaa M. Moursi , Jon Vanderwerff

The notion of a firmly nonexpansive mapping is central in fixed point theory because of attractive convergence properties for iterates and the correspondence with maximal monotone operators due to Minty. In this paper, we systematically…

Functional Analysis · Mathematics 2011-01-26 Heinz H. Bauschke , Sarah M. Moffat , Xianfu Wang

We propose a new method for low-rank approximation of Moore-Penrose pseudoinverses (MPPs) of large-scale matrices using tensor networks. The computed pseudoinverses can be useful for solving or preconditioning of large-scale overdetermined…

Numerical Analysis · Mathematics 2016-07-06 Namgil Lee , Andrzej Cichocki

Compared to the entrywise transforms which preserve positive semidefiniteness, those leaving invariant the inertia of symmetric matrices reveal a surprising rigidity. We first obtain the classification of negativity preservers by combining…

Classical Analysis and ODEs · Mathematics 2026-04-14 Alexander Belton , Dominique Guillot , Apoorva Khare , Mihai Putinar

Nonexpansive mappings play a central role in modern optimization and monotone operator theory because their fixed points can describe solutions to optimization or critical point problems. It is known that when the mappings are sufficiently…

Functional Analysis · Mathematics 2020-04-28 Salihah Alwadani , Heinz H. Bauschke , Xianfu Wang

For two positive definite adjointable operators $M$ and $N$, and an adjointable operator $A$ acting on a Hilbert $C^*$-module, some properties of the weighted Moore-Penrose inverse $A^\dag_{MN}$ are established. When $A=(A_{ij})$ is…

Operator Algebras · Mathematics 2012-08-01 Qingxiang Xu , Yonghao Chen , Chuanning Song

Accretive and monotone operator theory are central branches of nonlinear functional analysis and constitute the abstract study of set-valued mappings between function spaces. This paper deals with the computational properties of certain…

Logic · Mathematics 2022-05-10 Nicholas Pischke

An operator convex function on (0,\infty) which satisfies the symmetry condition k(1/x) = x k(x) can be used to define a type of non-commutative multiplication by a positive definite matrix (or its inverse) using the primitive concepts of…

Quantum Physics · Physics 2021-12-28 Fumio Hiai , Hideki Kosaki , Denes Petz , Mary Beth Ruskai

Some concepts, such as non-compactness measure and condensing operators, defined on metric spaces are extended to uniform spaces. Such extensions allow us to locate, in the context of uniform spaces, some classical results existing in…

General Topology · Mathematics 2015-11-25 Raúl Fierro

The theory and computation of tensors with different tensor products play increasingly important roles in scientific computing and machine learning. Different products aim to preserve different algebraic properties from the matrix algebra,…