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We obtain a general concept of triplet of Hilbert spaces with closed (unbounded) embeddings instead of continuous (bounded) ones. The construction starts with a positive selfadjoint operator $H$, that is called the Hamiltonian of the…

Functional Analysis · Mathematics 2025-11-04 Petru Cojuhari , Aurelian Gheondea

We consider the problem of maximizing a convex function over a closed convex set in a real Hilbert space. For linear functions, we show that a single orthogonal projection suffices to obtain an approximate solution. For continuous convex…

Optimization and Control · Mathematics 2026-02-23 Pedro Felzenszwalb , Heon Lee

In this article we present a modified S-iteration process that we combine with inertial extrapolation to find a common solution to the split monotone inclusion problem and the fixed point problem in real Hilbert space.Our goal is to…

Numerical Analysis · Mathematics 2021-10-11 Shamshad Husain , Uqba Rafat

In this article we develop a max-strategy improvement algorithm for computing least fixpoints of operators on on the reals that are point-wise maxima of finitely many monotone and order-concave operators. Computing the uniquely determined…

Programming Languages · Computer Science 2012-04-06 Thomas Martin Gawlitza , Helmut Seidl

Operator learning has been highly successful for continuous mappings between infinite-dimensional spaces, such as PDE solution operators. However, many operators of interest-including differential operators-are discontinuous or set-valued,…

Machine Learning · Computer Science 2026-05-13 Takashi Furuya , Yury Korolev , Takaharu Yaguchi

We investigate two greedy strategies for finding an approximation to the minimum of a convex function $E$ defined on a Hilbert space $H$. We prove convergence rates for these algorithms under suitable conditions on the objective function…

Numerical Analysis · Mathematics 2014-01-09 Hao Nguyen , Guergana Petrova

The theorem on the existence of maximal nonnegative invariant subspaces for a special class of dissipative operators in Hilbert space with indefinite inner product is proved in the paper. It is shown in addition that the spectra of the…

Functional Analysis · Mathematics 2007-05-23 A. A. Shkalikov

We propose an extended forward-backward algorithm for approximating a zero of a maximal monotone operator which can be split as the extended sum of two maximal monotone operators. We establish the weak convergence in average of the sequence…

Optimization and Control · Mathematics 2013-06-25 Marc Lassonde , Ludovic Nagesseur

We study the spectral properties of positive absolutely minimum attaining operators defined on infinite dimensional complex Hilbert spaces and using that derive a characterization theorem for such type of operators. We construct several…

Spectral Theory · Mathematics 2017-11-07 J. Ganesh , G. Ramesh , D. Sukumar

In this article, we propose a Krasnosel'ski\v{\i}-Mann-type algorithm for finding a common fixed point of a countably infinite family of nonexpansive operators $(T_n)_{n \geq 0}$ in Hilbert spaces. We formulate an asymptotic property which…

Optimization and Control · Mathematics 2019-11-27 Radu Ioan Bot , Dennis Meier

The paper investigates two inertial extragradient algorithms for seeking a common solution to a variational inequality problem involving a monotone and Lipschitz continuous mapping and a fixed point problem with a demicontractive mapping in…

Optimization and Control · Mathematics 2023-08-08 Bing Tan , Liya Liu , Xiaolong Qin

In this work, we consider a class of convex optimization problems in a real Hilbert space that can be solved by performing a single projection, i.e., by projecting an infeasible point onto the feasible set. Our results improve those…

Optimization and Control · Mathematics 2024-04-10 Hoa T. Bui , Regina S. Burachik , Evgeni A. Nurminski , Matthew K. Tam

We present several matrix and operator inequalities of Hermite-Hadamard type. We first establish a majorization version for monotone convex functions on matrices. We then utilize the Mond-Pecaric method to get an operator version for convex…

Functional Analysis · Mathematics 2013-04-02 Mohammad Sal Moslehian

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

This document introduces a strategy to solve linear optimization problems. The strategy is based on the bounding condition each constraint produces on each one of the problem's dimension. The solution of a linear optimization problem is…

Optimization and Control · Mathematics 2018-09-24 Gerardo L. Febres

In this paper, we consider the quadratic programming problems under finitely many convex quadratic constraints in Hilbert spaces. By using the Legendre property of quadratic forms or the compactness of operators in the presentations of…

Optimization and Control · Mathematics 2016-05-03 Vu Van Dong , Nguyen Nang Tam

This paper considers a networked system with a finite number of users and supposes that each user tries to minimize its own private objective function over its own private constraint set. It is assumed that each user's constraint set can be…

Optimization and Control · Mathematics 2015-10-22 Hideaki Iiduka

We propose and study a strongly convergent inexact inertial projective splitting (PS) algorithm for finding zeros of composite monotone inclusion problems involving the sum of finitely many maximal monotone operators. Strong convergence of…

Optimization and Control · Mathematics 2025-07-09 M. Marques Alves , J. E. Navarro Caballero , R. T. Marcavillaca

In this note, we provide some sufficient and necessary conditions for the core inverse of the perturbed operator to have the simplest possible expression. The results improve the recent work by H. Ma (Optimal perturbation bounds for the…

Functional Analysis · Mathematics 2018-07-05 Qianglian Huang , Saijie Chen , Lanping Zhu

Machine learning approaches relying on such criteria as adversarial robustness or multi-agent settings have raised the need for solving game-theoretic equilibrium problems. Of particular relevance to these applications are methods targeting…

Machine Learning · Computer Science 2023-10-27 Xufeng Cai , Ahmet Alacaoglu , Jelena Diakonikolas