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Overlap functions are a class of aggregation functions that measure the overlapping degree between two values. Interval-valued overlap functions were defined as an extension to express the overlapping of interval-valued data, and they have…

Artificial Intelligence · Computer Science 2021-06-09 Tiago da Cruz Asmus , Graçaliz Pereira Dimuro , Benjamín Bedregal , José Antonio Sanz , Radko Mesiar , Humberto Bustince

The operator product expansion (OPE) in 4d (super)conformal field theory is of broad interest, for both formal and phenomenological applications. In this paper, we use conformal perturbation theory to study the OPE of nearly-free fields…

High Energy Physics - Theory · Physics 2015-06-04 Daniel Green , David Shih

Perspective functions arise explicitly or implicitly in various forms in applied mathematics and in statistical data analysis. To date, no systematic strategy is available to solve the associated, typically nonsmooth, optimization problems.…

Optimization and Control · Mathematics 2016-12-15 Patrick L. Combettes , Christian L. Müller

In this paper, we introduce a new operator, $\mathcal{S}$, which is closely related to the restriction problem for spheres in $\mathbb{F}_q^d$, the $d$-dimensional vector space over the finite field $\mathbb{F}_q$ with $q$ elements. The…

Classical Analysis and ODEs · Mathematics 2025-02-19 Hunseok Kang , Doowon Koh

Quantifying the influence of infinitesimal changes in training data on model performance is crucial for understanding and improving machine learning models. In this work, we reformulate this problem as a weighted empirical risk minimization…

Machine Learning · Computer Science 2025-04-11 Omri Lev , Ashia C. Wilson

Convex regression is a method for estimating the convex function from a data set. This method has played an important role in operations research, economics, machine learning, and many other areas. However, it has been empirically observed…

Methodology · Statistics 2024-10-17 Zhiqiang Liao , Sheng Dai , Eunji Lim , Timo Kuosmanen

The paper examines the construction and analysis of a new class of mixed exponential statistical structures that combine the properties of stochastic models and linear positive operators. The relevance of the topic is driven by the growing…

Statistics Theory · Mathematics 2025-12-30 Yurii Volkov , Oleksandr Volkov , Nataliia Voinalovych

We consider the application of feedback control strategies with point actuators to stabilise desired interface shapes. We take a multidimensional Kuramoto--Sivashinsky equation as a test case; this equation arises in the study of thin…

Optimization and Control · Mathematics 2019-01-29 Ruben J. Tomlin , Susana N. Gomes

In [R. J. Baraldi and D. P. Kouri, Math. Program., 201:1 (2023), pp. 559-598], the authors introduced a trust-region method for minimizing the sum of a smooth nonconvex and a nonsmooth convex function, the latter of which has an analytical…

Optimization and Control · Mathematics 2026-01-15 Leandro Farias Maia , Robert Baraldi , Drew P. Kouri

We consider nonconforming methods for symmetric elliptic problems and characterize their quasi-optimality in terms of suitable notions of stability and consistency. The quasi-optimality constant is determined and the possible impact of…

Numerical Analysis · Mathematics 2017-10-11 Andreas Veeser , Pietro Zanotti

We study minimax lower bounds for function estimation problems on large graph when the target function is smoothly varying over the graph. We derive minimax rates in the context of regression and classification problems on graphs that…

Statistics Theory · Mathematics 2018-02-16 Alisa Kirichenko , Harry van Zanten

It is expected that conformal symmetry is an emergent property of many systems at their critical point. This imposes strong constraints on the critical behavior of a given system. Taking them into account in theoretical approaches can lead…

Statistical Mechanics · Physics 2024-06-26 Bertrand Delamotte , Gonzalo De Polsi , Matthieu Tissier , Nicolás Wschebor

Given additional distributional information in the form of moment restrictions, kernel density and distribution function estimators with implied generalised empirical likelihood probabilities as weights achieve a reduction in variance due…

Methodology · Statistics 2019-10-08 Vitaliy Oryshchenko , Richard J. Smith

We discuss ways in which momentum operators can be introduced on an oriented metric graph. A necessary condition appears to the balanced property, or a matching between the numbers of incoming and outgoing edges; we show that a graph…

Mathematical Physics · Physics 2020-02-07 Pavel Exner

Many studies have been conducted on statistical convergence, and it remains an area of active research. Since its introduction, statistical convergence has found applications many fields. Nevertheless, there is a shortage of research…

Functional Analysis · Mathematics 2024-06-14 Erdal Bayram , Mehmet Küçükaslan , Mikail Et , Abdullah Aydın

Superconformal transformations are derived for the $\N=2,4 supermultiplets corresponding to the simplest chiral primary operators. These are applied to two, three and four point correlation functions. When $\N=4$, results are obtained for…

High Energy Physics - Theory · Physics 2009-11-07 F. A. Dolan , H. Osborn

We introduce an algorithm of joint approximation of a function and its first derivative by alternative orthogonal polynomials on the interval [0,1].The algorithm exhibits properties of shape preserving approximation for the function. A weak…

Numerical Analysis · Mathematics 2020-01-14 Vladimir S. Chelyshkov

We study the momentum-space 4-point correlation function of identical scalar operators in conformal field theory. Working specifically with null momenta, we show that its imaginary part admits an expansion in conformal blocks. The blocks…

High Energy Physics - Theory · Physics 2020-12-29 Marc Gillioz

In many image analysis problems, the contours of objects carry important statistical information about shape. Such contours are typically affected by deformation variables including scaling, translation, rotation, and reparametrization.…

Methodology · Statistics 2026-05-26 Issam-Ali Moindjié , Cédric Beaulac , Marie-Hélène Descary

Lifting operators play an important role in starting a lattice Boltzmann model from a given initial density. The density, a macroscopic variable, needs to be mapped to the distribution functions, mesoscopic variables, of the lattice…

Computational Engineering, Finance, and Science · Computer Science 2012-09-18 Ynte Vanderhoydonc , Wim Vanroose