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In this work, we develop a unified framework for quasidiagonal and F\o lner-type approximations of linear operators on Hilbert spaces. These approximations (originally formulated for bounded operators and operator algebras) involve…

Functional Analysis · Mathematics 2025-09-04 Eva A. Gallardo-Gutiérrez , Fernando Lledó , Laura Sáenz

In this work, an operator superquadratic function (in operator sense) for positive Hilbert space operators is defined. Several examples with some important properties together with some observations which are related to the operator…

Functional Analysis · Mathematics 2019-12-17 M. W. Alomari

In minimization models for image recovery and data analysis problems, loss functions and linear operators are typically aggregated as an average of composite terms. Each term in the aggregate models a desired property of the ideal solution…

Optimization and Control · Mathematics 2026-02-26 Patrick L. Combettes , Diego J. Cornejo

We propose a method for solving constrained fixed point problems involving compositions of Lipschitz pseudo contractive and firmly nonexpansive operators in Hilbert spaces. Each iteration of the method uses separate evaluations of these…

Optimization and Control · Mathematics 2011-01-10 Luis M. Briceño-Arias

We consider minimizing a function consisting of a quadratic term and a proximable term which is possibly nonconvex and nonsmooth. This problem is also known as scaled proximal operator. Despite its simple form, existing methods suffer from…

Optimization and Control · Mathematics 2024-03-01 Yiming Zhou , Wei Dai

In this paper we develop proximal methods for statistical learning. Proximal point algorithms are useful in statistics and machine learning for obtaining optimization solutions for composite functions. Our approach exploits closed-form…

Machine Learning · Statistics 2015-06-02 Nicholas G. Polson , James G. Scott , Brandon T. Willard

The nonlinear conjugate gradient methods are known to be an effective approach for standard unconstrained optimization problems especially for large-scale problems. This paper proposes a proximal nonlinear conjugate gradient method, which…

Optimization and Control · Mathematics 2026-04-14 Shodai Hamana , Yasushi Narushima

We introduce certain linear positive operators and study some approximation properties of these operators in the space of functions, continuous on a compact set, of two variables. We also find the order of this approximation by using…

Classical Analysis and ODEs · Mathematics 2007-09-24 Fatma Tasdelen , Ali Olgun , Gulen Bascanbaz-Tunca

Finite plane geometry is associated with finite dimensional Hilbert space. The association allows mapping of q-number Hilbert space observables to the c-number formalism of quantum mechanics in phase space. The mapped entities reflect…

Quantum Physics · Physics 2015-08-04 M. Revzen , A. Mann

In functional data analysis (FDA), covariance function is fundamental not only as a critical quantity for understanding elementary aspects of functional data but also as an indispensable ingredient for many advanced FDA methods. This paper…

Methodology · Statistics 2017-01-24 Raymond K. W. Wong , Xiaoke Zhang

The benefits of cutting planes based on the perspective function are well known for many specific classes of mixed-integer nonlinear programs with on/off structures. However, we are not aware of any empirical studies that evaluate their…

Optimization and Control · Mathematics 2021-03-18 Ksenia Bestuzheva , Ambros Gleixner , Stefan Vigerske

Given a set of matrices, modeled as samples of a matrix-valued function, we suggest a method to approximate the underline function using a product approximation operator. This operator extends known approximation methods by exploiting the…

Numerical Analysis · Mathematics 2016-11-15 Nira Dyn , Uri Itai , Nir Sharon

We introduce and analyze an abstract algorithm that aims to find the projection onto a closed convex subset of a Hilbert space. When specialized to the fixed point set of a quasi nonexpansive mapping, the required sufficient condition…

Functional Analysis · Mathematics 2012-11-08 Heinz H. Bauschke , Jiawei Chen , Xianfu Wang

The MM principle is a device for creating optimization algorithms satisfying the ascent or descent property. The current survey emphasizes the role of the MM principle in nonlinear programming. For smooth functions, one can construct an…

Optimization and Control · Mathematics 2015-07-29 Kenneth Lange , Kevin L. Keys

This paper demonstrates that the space of piecewise smooth functions can be well approximated by the space of functions defined by a set of simple (non-linear) operations on smooth uniform splines. The examples include bivariate functions…

Numerical Analysis · Mathematics 2024-05-13 David Levin

In computational practice, most attention is paid to rational approximations of functions and approximations by the sum of exponents. We consider a wide enough class of nonlinear approximations characterized by a set of two required…

Numerical Analysis · Mathematics 2023-01-18 Petr N. Vabishchevich

In this paper the notion of an abstract square function (estimate) is introduced as an operator X to gamma (H; Y), where X, Y are Banach spaces, H is a Hilbert space, and gamma(H; Y) is the space of gamma-radonifying operators. By the…

Functional Analysis · Mathematics 2013-11-05 Bernhard Hermann Haak , Markus Haase

In this article, we first study, in the framework of operator theory, Pusz and Woronowicz's functional calculus for pairs of bounded positive operators on Hilbert spaces associated with a homogeneous two-variable function on $[0,\infty)^2$.…

Functional Analysis · Mathematics 2021-05-21 Fumio Hiai , Yoshimichi Ueda , Shuhei Wada

If $\H$ is a Hilbert space, $A$ is a positive bounded linear operator on $\cH$ and $\cS$ is a closed subspace of $\cH$, the relative position between $\cS$ and $A^{-1}(\cS \orto)$ establishes a notion of compatibility. We show that the…

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

A space-filling function is a bijection from the unit line segment to the unit square, cube, or hypercube. The function from the unit line segment is continuous. The inverse function, while well-defined, is not continuous. Space-filling…

Computational Geometry · Computer Science 2015-04-21 Aubrey Jaffer