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We obtain approximation results for general positive linear operators satisfying mild conditions, when acting on discontinuous functions and absolutely continuous functions having discontinuous derivatives. The upper bounds, given in terms…

Probability · Mathematics 2024-10-29 José A. Adell , P. Garrancho , F. J. Martínez-Sánchez

In this paper we focus on the convergence analysis of the forward-backward splitting method for solving nonsmooth optimization problems in Hilbert spaces when the objective function is the sum of two convex functions. Assuming that one of…

Optimization and Control · Mathematics 2016-10-17 J. Y. Bello Cruz , T. T. A. Nghia

We introduce a notion of completely bounded holomorphic functions defined on the open unit ball of an operator space. We endow the set of these functions with an operator space structure, and in the scalar-valued case we identify an…

Functional Analysis · Mathematics 2024-05-16 Javier Alejandro Chávez-Domínguez , Verónica Dimant

The great advances of learning-based approaches in image processing and computer vision are largely based on deeply nested networks that compose linear transfer functions with suitable non-linearities. Interestingly, the most frequently…

Computer Vision and Pattern Recognition · Computer Science 2018-03-26 Peter Ochs , Tim Meinhardt , Laura Leal-Taixe , Michael Moeller

Stators, which may be intuitively defined as "half states, half operators" are mathematical objects which act on two Hilbert spaces and utilize entanglement to create remote operations and exchange information between two physical systems.…

Quantum Physics · Physics 2017-02-21 Erez Zohar

Operator convex functions defined on the positive half-line play a prominent role in the theory of quantum information, where they are used to define quantum $f$-divergences. Such functions admit integral representations in terms of…

Optimization and Control · Mathematics 2023-05-23 Oisín Faust , Hamza Fawzi

This paper investigates the computation of proximity operators for scale and signed permutation invariant functions. A scale-invariant function remains unchanged under uniform scaling, while a signed permutation invariant function retains…

Optimization and Control · Mathematics 2024-04-02 Jianqing Jia , Ashley Prater-Bennette , Lixin Shen

The concept of proximate order is widely used in the theories of entire, meromorphic, subharmonic and plurisubharmonic functions. We give a general interpretation of this concept as a proximate growth function relative to a model growth…

Complex Variables · Mathematics 2019-12-03 Bulat N. Khabibullin

In this paper we study some geometric properties like parallelism, orthogonality and semi-rotundity in the space of bounded linear operators. We completely characterize parallelism of two compact linear operators between normed linear…

Functional Analysis · Mathematics 2024-08-13 Arpita Mal , Debmalya Sain , Kallol Paul

Integral transforms are invaluable mathematical tools to map functions into spaces where they are easier to characterize. We introduce the hyperdimensional transform as a new kind of integral transform. It converts square-integrable…

Machine Learning · Computer Science 2023-10-26 Pieter Dewulf , Michiel Stock , Bernard De Baets

The purpose of the article is to generalize the concept of approximate Birkhoff-James orthogonality, in the semi-Hilbertian structure. Given a positive operator $ A $ on a Hilbert space $ \mathbb{H}, $ we define $ (\epsilon,A)- $approximate…

Functional Analysis · Mathematics 2024-08-14 Jeet Sen , Debmalya Sain , Kallol Paul

In this paper, we discuss the problem of minimizing the sum of two convex functions: a smooth function plus a non-smooth function. Further, the smooth part can be expressed by the average of a large number of smooth component functions, and…

Machine Learning · Computer Science 2016-11-17 Luo Luo , Zihao Chen , Zhihua Zhang , Wu-Jun Li

An efficient computer algorithm is described for the perspective drawing of a wide class of surfaces. The class includes surfaces corresponding lo single-valued, continuous functions which are defined over rectangular domains. The algorithm…

Graphics · Computer Science 2011-07-29 Ignacio Vega-Paez , Jose Angel Ortega , Georgina G. Pulido

We propose a proximal approach to deal with a class of convex variational problems involving nonlinear constraints. A large family of constraints, proven to be effective in the solution of inverse problems, can be expressed as the lower…

Numerical Analysis · Computer Science 2014-03-21 Giovanni Chierchia , Nelly Pustelnik , Jean-Christophe Pesquet , Béatrice Pesquet-Popescu

Operator splitting algorithms are a cornerstone of modern first-order optimization, relying critically on proximal operators as their fundamental building blocks. However, explicit formulas for proximal operators are available only for…

Optimization and Control · Mathematics 2025-09-17 Nicholas Di , Eric C. Chi , Samy Wu Fung

A quasi-Hermitian operator is an operator that is similar to its adjoint in some sense, via a metric operator, i.e., a strictly positive self-adjoint operator. Whereas those metric operators are in general assumed to be bounded, we analyze…

Mathematical Physics · Physics 2016-10-24 Jean-Pierre Antoine , Camillo Trapani

In this paper we study dual bases functions in subspaces. These are bases which are dual to functionals on larger linear space. Our goal is construct and derive properties of certain bases obtained from the construction, with primary focus…

Numerical Analysis · Mathematics 2017-04-28 Scott N. Kersey

In the context of functional data analysis, probability density functions as non-negative functions are characterized by specific properties of scale invariance and relative scale which enable to represent them with the unit integral…

Numerical Analysis · Mathematics 2019-12-19 Jitka Machalova , Renata Talska , Karel Hron , Ales Gaba

The Koopman operator is a mathematical tool that allows for a linear description of non-linear systems, but working in infinite dimensional spaces. Dynamic Mode Decomposition and Extended Dynamic Mode Decomposition are amongst the most…

Machine Learning · Computer Science 2021-03-26 Francesco Zanini , Alessandro Chiuso

The projection onto the epigraph or a level set of a closed proper convex function can be achieved by finding a root of a scalar equation that involves the proximal operator as a function of the proximal parameter. This paper develops the…

Optimization and Control · Mathematics 2021-02-16 Michael P. Friedlander , Ariel Goodwin , Tim Hoheisel
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