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The main object of this paper is to construct new Durrmeyer type operators which have better features than the classical one. Some results concerning the rate of convergence and asymptotic formulas of the new operator are given. Finally,…

Numerical Analysis · Mathematics 2018-10-17 Ana Maria Acu , Vijay Gupta , Gancho Tachev

The aim of this paper is to present some new Fejer-type results for convex functions. Improvements of Young's inequality (the arithmetic-geometric mean inequality) and other applications to special means are pointed as well.

Classical Analysis and ODEs · Mathematics 2012-03-22 N. Minculete , F. -C. Mitroi

We construct explicit easily implementable polynomial approximations of sufficiently high accuracy for locally constant functions on the union of disjoint segments. This problem has important applications in several areas of numerical…

Functional Analysis · Mathematics 2023-11-29 Yuri Malykhin , Konstantin Ryutin

The topics of Convexity and Concavity and Envelopes are central in Complex Analysis and extensively investigated. The aim of this paper is to find a possible counterpart in Algebraic Geometry. The article presents preliminary results on…

Complex Variables · Mathematics 2025-11-12 Giuseppe Tomassini

A broader definition of generalized truncations of graphs is introduced followed by an exploration of some standard concepts and parameters with regard to generalized truncations.

Combinatorics · Mathematics 2020-07-10 Brian Alspach , Joshua B. Connor

The convergence of the algorithm for solving convex feasibility problem is studied by the method of sequential averaged and relaxed projections. Some results of H. H. Bauschke and J. M. Borwein are generalized by introducing new methods.…

Metric Geometry · Mathematics 2007-09-18 Ryszard Szwarc

We investigate graph representation learning approaches that enable models to generalize across graphs: given a model trained using the representations from one graph, our goal is to apply inference using those same model parameters when…

Machine Learning · Computer Science 2023-02-20 Anton Amirov , Chris Quirk , Jennifer Neville

Many algorithms and applications involve repeatedly solving variations of the same inference problem; for example we may want to introduce new evidence to the model or perform updates to conditional dependencies. The goal of adaptive…

Data Structures and Algorithms · Computer Science 2012-06-18 Umut A. Acar , Alexander T. Ihler , Ramgopal Mettu , Ozgur Sumer

A matrix approach to continuous iteration is proposed for general formal series. It leads, in particular, to an order{to{order iteration of the exponential function, and consequently to an algorithmic approach to tetration. Lower{order…

Mathematical Physics · Physics 2014-10-16 R. Aldrovandi

This article presents a novel, general, and effective simulation-inspired approach, called {\it repro samples method}, to conduct statistical inference. The approach studies the performance of artificial samples, referred to as {\it repro…

Methodology · Statistics 2022-06-15 Min-ge Xie , Peng Wang

A stochastic gradient method for finite-sum minimization subject to deterministic linear constraints is proposed and analyzed. The procedure presented adapts the projected gradient method on convex set to the use of both a stochastic…

Optimization and Control · Mathematics 2026-05-19 Natasa Krklec Jerinkic , Benedetta Morini , Mahsa Yousefi

We study the usage of regularity properties of collections of sets in convergence analysis of alternating projection methods for solving feasibility problems. Several equivalent characterizations of these properties are provided. Two…

Optimization and Control · Mathematics 2018-02-27 Alexander Y. Kruger , Nguyen H. Thao

The theory of abstract convexity, also known as convexity without linearity, is an extension of the classical convex analysis. There are a number of remarkable results, mostly concerning duality, and some numerical methods, however, this…

Optimization and Control · Mathematics 2025-02-20 Reinier Díaz Millán , Nadezda Sukhorukova , Julien Ugon

Fibonacci sequence, generated by summing the preceding two terms, is a classical sequence renowned for its elegant properties. In this paper, leveraging properties of generalized Fibonacci sequences and formulas for consecutive sums of…

Combinatorics · Mathematics 2026-04-28 Zixian Yang , Jianchao Bai

System modeling is a classical approach to ensure their reliability since it is suitable both for a formal verification and for software testing techniques. In the context of model-based testing an approach combining random testing and…

Software Engineering · Computer Science 2018-06-14 Julien Bernard , Pierre-Cyrille Héam , Olga Kouchnarenko

Constraint Acquisition (CA) aims to widen the use of constraint programming by assisting users in the modeling process. However, most CA methods suffer from a significant drawback: they learn a single set of individual constraints for a…

Artificial Intelligence · Computer Science 2024-12-20 Dimos Tsouros , Senne Berden , Steven Prestwich , Tias Guns

Graphs are used in many disciplines to model the relationships that exist between objects in a complex discrete system. Researchers may wish to compare a network of interest to a "typical" graph from a family (or ensemble) of graphs which…

Combinatorics · Mathematics 2025-08-08 Catherine Greenhill

We consider the problem of projecting a convex set onto a subspace, or equivalently formulated, the problem of computing a set obtained by applying a linear mapping to a convex feasible set. This includes the problem of approximating convex…

Optimization and Control · Mathematics 2024-12-11 Gabriela Kováčová , Birgit Rudloff

Statistically resolving the underlying haplotype pair for a genotype measurement is an important intermediate step in gene mapping studies, and has received much attention recently. Consequently, a variety of methods for this problem have…

Machine Learning · Computer Science 2007-10-29 Matti Kääriäinen , Niels Landwehr , Sampsa Lappalainen , Taneli Mielikäinen

In this paper, we propose new accelerated methods for smooth convex optimization, called contracting proximal methods. At every step of these methods, we need to minimize a contracted version of the objective function augmented by a…

Optimization and Control · Mathematics 2021-05-21 Nikita Doikov , Yurii Nesterov
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