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In this article we study two "strong" topologies for spaces of smooth functions from a finite-dimensional manifold to a (possibly infinite-dimensional) manifold modeled on a locally convex space. Namely, we construct Whitney type topologies…

General Topology · Mathematics 2018-05-14 Eivind Otto Hjelle , Alexander Schmeding

We introduce a fixed point iteration process built on optimization of a linear function over a compact domain. We prove the process always converges to a fixed point and explore the set of fixed points in various convex sets. In particular,…

Optimization and Control · Mathematics 2021-03-18 Pedro Felzenszwalb , Caroline Klivans , Alice Paul

It is shown that if $C$ is a nonempty convex and weakly compact subset of a Banach space $X$ with $M(X)>1$ and $T:C\rightarrow C$ satisfies condition $(C)$ or is continuous and satisfies condition $(C_{\lambda})$ for some $\lambda \in…

Functional Analysis · Mathematics 2015-11-24 Anna Betiuk-Pilarska , Andrzej Wiśnicki

The use of min-max optimization in adversarial training of deep neural network classifiers and training of generative adversarial networks has motivated the study of nonconvex-nonconcave optimization objectives, which frequently arise in…

Optimization and Control · Mathematics 2021-03-02 Jelena Diakonikolas , Constantinos Daskalakis , Michael I. Jordan

The objective of ordinal embedding is to find a Euclidean representation of a set of abstract items, using only answers to triplet comparisons of the form "Is item $i$ closer to the item $j$ or item $k$?". In recent years, numerous…

Machine Learning · Computer Science 2021-10-22 Leena Chennuru Vankadara , Siavash Haghiri , Michael Lohaus , Faiz Ul Wahab , Ulrike von Luxburg

A game theory inspired methodology is proposed for finding a function's saddle points. While explicit descent methods are known to have severe convergence issues, implicit methods are natural in an adversarial setting, as they take the…

Optimization and Control · Mathematics 2019-06-04 Montacer Essid , Esteban Tabak , Giulio Trigila

In this paper, we introduce a new problem called the split feasibility and fixed point equality problems (SFFPEP) and propose a new iterative algorithm for solving the problem (SFFPEP) for the class of quasi-nonexpansive mappings in Hilbert…

Functional Analysis · Mathematics 2016-10-10 L. B. Mohammed , A. Kılıçman

Within the framework on non-extensive thermostatistics we revisit the recently advanced q-duality concept. We focus our attention here on a modified q-entropic measure of the spatial inhomogeneity for binary patterns. At a fixed…

Statistical Mechanics · Physics 2015-06-24 R. Piasecki , A. Plastino

In this paper we propose two strongly convergent parallel hybrid iterative methods for finding a common element of the set of fixed points of a family of quasi $\phi$-asymptotically nonexpansive mappings $\{F(S_j)\}_{j=1}^N$, the set of…

Optimization and Control · Mathematics 2015-10-28 Pham Ky Anh , Dang Van Hieu

This paper considers the fixed point problem for a nonexpansive mapping on a real Hilbert space and proposes novel line search fixed point algorithms to accelerate the search. The termination conditions for the line search are based on the…

Optimization and Control · Mathematics 2015-09-21 Hideaki Iiduka

The purpose of this paper is to propose and analyze a multi-step iterative algorithm to solve a convex optimization problem and a fixed point problem posed on a Hadamard space. The convergence properties of the proposed algorithm are…

Functional Analysis · Mathematics 2018-02-28 Muhammad Aqeel Ahmad Khan , Hafiza Arham Maqbool

To a formally smooth algebra A we associate a quiver setting (Q,a) containing enough information to reconstruct all the local quiver settings determining the etale local structure of finite dimensional representation schemes of A, see…

Rings and Algebras · Mathematics 2007-05-23 Lieven Le Bruyn

In this paper, we introduce the concepts of m-quasiconvex, originally m-quasiconvex,and generalized m-quasiconvex functionals on topological vector spaces. Then we extend the concept of point separable topological vector spaces (by the…

Functional Analysis · Mathematics 2020-12-07 Jinlu Li

This study first defines a new metric with normal structure on C(H,K) and then a new technique to prove fixed point theorems for families of non-expansive maps on this metric space. Indeed, it shows that the presence of a bounded orbit…

Functional Analysis · Mathematics 2016-02-15 Mona Nabiei

Ordinal embedding aims at finding a low dimensional representation of objects from a set of constraints of the form "item $j$ is closer to item $i$ than item $k$". Typically, each object is mapped onto a point vector in a low dimensional…

Machine Learning · Computer Science 2021-05-26 Aïssatou Diallo , Johannes Fürnkranz

We consider projection algorithms for solving (nonconvex) feasibility problems in Euclidean spaces. Of special interest are the Method of Alternating Projections (MAP) and the Douglas-Rachford or Averaged Alternating Reflection Algorithm…

Optimization and Control · Mathematics 2014-03-17 Robert Hesse , D. Russell Luke

The concept of quasi-partial b-metric-like spaces is being introduced and studied with the help of topology. Examples are also discussed to support the results. Some fixed point theorems are proved in the setting of quasi-partial…

General Topology · Mathematics 2018-12-04 Anuradha Gupta , Manu Rohilla

In this paper, a novel parallel hybrid iterative method is proposed for finding a common element of the set of solutions of a system of equilibrium problems, the set of solutions of variational inequalities for inverse strongly monotone…

Optimization and Control · Mathematics 2015-10-28 Dang Van Hieu

We generalise the Atiyah-Segal-Singer fixed point theorem to noncompact manifolds. Using $KK$-theory, we extend the equivariant index to the noncompact setting, and obtain a fixed point formula for it. The fixed point formula is the…

K-Theory and Homology · Mathematics 2018-04-04 Peter Hochs , Hang Wang

Manifold learning is a hot research topic in the field of computer science and has many applications in the real world. A main drawback of manifold learning methods is, however, that there is no explicit mappings from the input data…

Computer Vision and Pattern Recognition · Computer Science 2010-01-18 Hong Qiao , Peng Zhang , Di Wang , Bo Zhang