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In this work, we propose a convenient framework for infinite-dimensional analysis (including both real and complex analysis in infinite dimensions), in which differentiation (in some weak sense) and integration operations can be easily…

Functional Analysis · Mathematics 2024-12-03 Jiayang Yu , Xu Zhang

In a partially ordered semigroup with the duality (or polarity) transform, it is possible to define a generalisation of continued fractions. General sufficient conditions for convergence of continued fractions with deterministic terms are…

Metric Geometry · Mathematics 2014-09-08 Ilya Molchanov

We study reduction schemes for functions of "many" variables into system of functions in one variable. Our setting includes infinite-dimensions. Following Cybenko-Kolmogorov, the outline for our results is as follows: We present explicit…

Functional Analysis · Mathematics 2019-03-08 Palle Jorgensen , Feng Tian

In this paper, we present a novel concept of the Fenchel conjugate for set-valued mappings and investigate its properties in finite and infinite dimensions. After establishing the fundamental properties of the Fenchel conjugate for…

Optimization and Control · Mathematics 2023-11-07 Nguyen Mau Nam , Gary Sandine , Nguyen Nang Thieu , Nguyen Dong Yen

We define convexity canonically in the setting of monoids. We show that many classical results from convex analysis hold for functions defined on such groups and semigroups, rather than only on vector spaces. Some examples and…

Optimization and Control · Mathematics 2015-10-16 Jonathan M. Borwein , Ohad Giladi

Valuations on the space of finite-valued convex functions on $\mathbb{C}^n$ that are continuous, dually epi-translation invariant, as well as $\mathrm{U}(n)$-invariant are completely classified. It is shown that the space of these…

Functional Analysis · Mathematics 2024-08-05 Jonas Knoerr

In this paper, we provide conditions under which one can take derivatives of the solution to convex optimization problems with respect to problem data. These conditions are (roughly) that Slater's condition holds, the functions involved are…

Optimization and Control · Mathematics 2019-11-13 Shane Barratt

We present an efficient algorithm for solving fractional programming problems whose objective functions are the ratio of a low-rank quadratic to a positive definite quadratic with convex constraints. The proposed algorithm for these…

Optimization and Control · Mathematics 2023-01-27 Ilya Krishtal , Brendan Miller

We derive new prox-functions on the simplex from additive random utility models of discrete choice. They are convex conjugates of the corresponding surplus functions. In particular, we explicitly derive the convexity parameter of discrete…

Optimization and Control · Mathematics 2019-09-13 David Müller , Yurii Nesterov , Vladimir Shikhman

It has been recently discovered that a convex function can be determined by its slopes and its infimum value, provided this latter is finite. The result was extended to nonconvex functions by replacing the infimum value by the set of all…

Functional Analysis · Mathematics 2025-10-21 Aris Daniilidis , David Salas , Sebastián Tapia-García

Any maximal monotone operator can be characterized by a convex function. The family of such convex functions is invariant under a transformation connected with the Fenchel-Legendre conjugation. We prove that there exist a convex…

Functional Analysis · Mathematics 2008-03-11 B. F. Svaiter

In this paper, we study randomized and cyclic coordinate descent for convex unconstrained optimization problems. We improve the known convergence rates in some cases by using the numerical semidefinite programming performance estimation…

Optimization and Control · Mathematics 2022-12-26 Hadi Abbaszadehpeivasti , Etienne de Klerk , Moslem Zamani

The decompositions of an element of a finite von Neumann algebra into the sum of a normal operator plus an s.o.t.-quasinilpotent operator, obtained using the Haagerup--Schultz hyperinvariant projections, behave well with respect to…

Operator Algebras · Mathematics 2013-10-10 Ken Dykema , Fedor Sukochev , Dmitriy Zanin

Successive quadratic approximations, or second-order proximal methods, are useful for minimizing functions that are a sum of a smooth part and a convex, possibly nonsmooth part that promotes regularization. Most analyses of iteration…

Optimization and Control · Mathematics 2019-01-25 Ching-pei Lee , Stephen J. Wright

A number of discrete and continuous optimization problems in machine learning are related to convex minimization problems under submodular constraints. In this paper, we deal with a submodular function with a directed graph structure, and…

Machine Learning · Computer Science 2013-09-27 Kiyohito Nagano , Yoshinobu Kawahara

This paper proposes a unique optimization approach for estimating the minimax rational approximation and its application for evaluating matrix functions. Our method enables the extension to generalized rational approximations and has the…

Numerical Analysis · Mathematics 2025-04-03 Nir Sharon , Vinesha Peiris , Nadia Sukhorukova , Julien Ugon

This paper is a detailed study of finite-dimensional modules defined on bicomplex numbers. A number of results are proved on bicomplex square matrices, linear operators, orthogonal bases, self-adjoint operators and Hilbert spaces, including…

Functional Analysis · Mathematics 2011-08-10 Raphael Gervais Lavoie , Louis Marchildon , Dominic Rochon

In this work we deal with set-valued functions with values in the power set of a separated locally convex space where a nontrivial pointed convex cone induces a partial order relation. A set-valued function is evenly convex if its epigraph…

Optimization and Control · Mathematics 2025-01-13 M. D. Fajardo

Detecting hidden convexity is one of the tools to address nonconvex minimization problems. After giving a formal definition of hidden convexity, we introduce the notion of conditional infimum, as it will prove instrumental in detecting…

Optimization and Control · Mathematics 2021-04-13 Jean-Philippe Chancelier , Michel de Lara

In this paper, we investigate the concept of p-convexity for sets and functions in n-dimensional Euclidean space. We establish novel algebraic and topological results within this generalized convexity framework. Furthermore, we analyze…

Optimization and Control · Mathematics 2026-04-14 Cristian Vera
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