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We prove that, any problem of minimization of proper lower semicontinuous function defined on a normal Hausdorff space, is canonically equivalent to a problem of minimization of a proper weak * lower semicontinuous convex function defined…

Functional Analysis · Mathematics 2017-05-24 Mohammed Bachir

In this paper we study the theory of operators on complex Hilbert spaces, which attain their minimum in the unit sphere. We prove some important results concerning the characterization of the N*, and also AN* operators, see respectively…

Functional Analysis · Mathematics 2013-05-16 Xavier Carvajal , Wladimir Neves

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

Frames have been investigated frequently over the last few decades due to their valuable properties, which are desirable for various applications as well as interesting for theory. Some applications additionally require distributed…

Functional Analysis · Mathematics 2024-07-09 Lukas Köhldorfer , Peter Balazs

We propose a variable metric framework for minimizing the sum of a self-concordant function and a possibly non-smooth convex function, endowed with an easily computable proximal operator. We theoretically establish the convergence of our…

Machine Learning · Statistics 2014-04-15 Quoc Tran-Dinh , Anastasios Kyrillidis , Volkan Cevher

We provide formulas for projectors onto a polyhedral set, i.e. the intersection of a finite number of halfspaces. To this aim we formulate the problem of finding the projection as a convex optimization problem and we solve explicitly…

Optimization and Control · Mathematics 2017-04-20 Krzysztof E. Rutkowski

A complete classification of continuous, dually epi-translation invariant, and rotation equivariant valuations on convex functions is established. This characterizes the recently introduced functional Minkowski vectors, which naturally…

Metric Geometry · Mathematics 2025-04-24 Mohamed A. Mouamine , Fabian Mussnig

This paper establishes three minimax theorems for possibly nonconvex functions on Euclidean spaces or on infinite-dimensional Hilbert spaces. The theorems also guarantee the existence of saddle points. As a by-product, a complete solution…

Optimization and Control · Mathematics 2025-10-31 Nguyen Nang Thieu , Nguyen Dong Yen

A broad range of inverse problems can be abstracted into the problem of minimizing the sum of several convex functions in a Hilbert space. We propose a proximal decomposition algorithm for solving this problem with an arbitrary number of…

Optimization and Control · Mathematics 2009-11-13 Patrick L. Combettes , Jean-Christophe Pesquet

We consider a stochastic version of the proximal point algorithm for optimization problems posed on a Hilbert space. A typical application of this is supervised learning. While the method is not new, it has not been extensively analyzed in…

Optimization and Control · Mathematics 2021-09-28 Monika Eisenmann , Tony Stillfjord , Måns Williamson

Operator-valued frames (or g-frames) are generalizations of frames and fusion frames and have been used in packets encoding, quantum computing, theory of coherent states and more. In this paper, we give a new formula for operator-valued…

Functional Analysis · Mathematics 2015-04-27 L. Gavruta , P. Gavruta

This article aims to explore the most recent developments in the study of the Hilbert matrix, acting as an operator on spaces of analytic functions and sequence spaces. We present the latest advances in this area, aiming to provide a…

Functional Analysis · Mathematics 2024-11-04 Carlo Bellavita , Vassilis Daskalogiannis , Georgios Stylogiannis

Making the gradients small is a fundamental optimization problem that has eluded unifying and simple convergence arguments in first-order optimization, so far primarily reserved for other convergence criteria, such as reducing the…

Optimization and Control · Mathematics 2021-01-29 Jelena Diakonikolas , Puqian Wang

Minimax optimization has been central in addressing various applications in machine learning, game theory, and control theory. Prior literature has thus far mainly focused on studying such problems in the continuous domain, e.g.,…

Optimization and Control · Mathematics 2021-11-03 Arman Adibi , Aryan Mokhtari , Hamed Hassani

It is well known that a strictly convex minimand admits at most one minimizer. We prove a partial converse: Let $X$ be a locally convex Hausdorff space and $f \colon X \mapsto \left( - \infty , \infty \right]$ a function with compact…

Optimization and Control · Mathematics 2023-03-23 Thomas Ruf , Bernd Schmidt

Given a unitary operator in a finite dimensional complex Hilbert space, its unitary reduction to a subspace is defined. The application to quantum graphs is discussed. It is shown how the reduction allows to generate the scattering matrices…

Quantum Physics · Physics 2025-01-10 L. L. Salcedo

The study of convex functions - in particular, of their optimization (really minimization) is one of the most important fields of applied mathematics. Convexity seems to be one of those incredibly well-chosen hypotheses which is just…

Optimization and Control · Mathematics 2026-03-11 Eigil Fjeldgren Rischel

Let $H$ be a real Hilbert space. In this short note, using some of the properties of bounded linear operators with closed range defined on $H$, certain bounds for a specific convex subset of the solution set of infinite linear…

Functional Analysis · Mathematics 2020-06-30 Projesh Nath Choudhury , M. Rajesh Kannan , K. C. Sivakumar

This paper is concerned with a certain aspect of the spectral theory of unitary operators in a Hilbert space and its aim is to give an explicit construction of continuous functions of unitary operators. Starting from a given unitary…

Functional Analysis · Mathematics 2014-03-11 Krzysztof Zajkowski

We show that minimizing a convex function over the integer points of a bounded convex set is polynomial in fixed dimension.

Optimization and Control · Mathematics 2012-03-20 Timm Oertel , Christian Wagner , Robert Weismantel