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Dimensional regularization of Euclidean momentum space integrals is a highly successful technique in renormalization of quantum field theories. While it yields a straightforward algorithmic method, with which to evaluate diagrams beyond…

Mathematical Physics · Physics 2020-09-03 Juuso Österman

We propose a unifying setting that combines existing restricted kernel machine methods into a single primal-dual multi-view framework for kernel principal component analysis in both supervised and unsupervised settings. We derive the primal…

Machine Learning · Computer Science 2023-07-07 Sonny Achten , Arun Pandey , Hannes De Meulemeester , Bart De Moor , Johan A. K. Suykens

Dyadic data is often encountered when quantities of interest are associated with the edges of a network. As such it plays an important role in statistics, econometrics and many other data science disciplines. We consider the problem of…

Statistics Theory · Mathematics 2023-10-17 Matias D. Cattaneo , Yingjie Feng , William G. Underwood

In this expository article, we briefly survey the main known schemes of proof of sparse domination principles within harmonic analysis. We then use the one based on the Calder\'on-Zygmund decomposition to prove a dual sparse domination…

Classical Analysis and ODEs · Mathematics 2025-09-10 Fernando Ballesta-Yagüe , José M. Conde-Alonso

The present work develops certain analytical tools required to construct and compute invariant kernels on the space of complex covariance matrices. The main result is the $\mathrm{L}^1$--Godement theorem, which states that any invariant…

Functional Analysis · Mathematics 2025-04-17 Salem Said , Franziskus Steinert , Cyrus Mostajeran

In this paper, we provide modulated interaction energy estimates for the kernel $K(x) = |x|^{-\alpha}$ with $\alpha \in (0,d)$, and its applications to quantified asymptotic analyses for kinetic equations. The proof relies on a dimension…

Analysis of PDEs · Mathematics 2021-12-24 Young-Pil Choi , Jinwook Jung

We consider the quantum inverse scattering method for several mixed integrable models based on the rational SU(N) R-matrix with general toroidal boundary conditions. This includes systems whose Hilbert spaces are invariant by the discrete…

Exactly Solvable and Integrable Systems · Physics 2009-11-10 G. A. P. Ribeiro , M. J. Martins

In the theory of inner and outer balayage of positive Radon measures on a locally compact space $X$ to arbitrary $A\subset X$ with respect to suitable, quite general function kernels, developed in a series of the author's recent papers, we…

Classical Analysis and ODEs · Mathematics 2024-07-23 Natalia Zorii

We develop a rough-path framework for two-parameter rough differential equations on rectangular and simplicial domains, motivated by the signature kernel and Schwinger--Dyson kernel equations. The theory is formulated in spaces of jointly…

Probability · Mathematics 2026-05-12 Thomas Cass , Dan Crisan , Andrea Iannucci , William F. Turner

We study singular integral operators with variable Calder\'on--Zygmund kernels and their commutators with $VMO$ functions in the framework of Orlicz spaces. After revisiting the classical $L^p$ theory, we establish boundedness results in…

Analysis of PDEs · Mathematics 2026-05-26 Amiran Gogatishvili , Pia Salerno , Lubomira Softova

This paper presents a framework based on matrices of monoids for the study of coupled cell networks. We formally prove within the proposed framework, that the set of results about invariant synchrony patterns for unweighted networks also…

Multiagent Systems · Computer Science 2022-01-13 Pedro M. Sequeira , António P. Aguiar , João Hespanha

In this article we extend the theory of lax monoidal structures, also known as multitensors, and the monads on categories of enriched graphs that they give rise to. Our first principal result -- the lifting theorem for multitensors --…

Category Theory · Mathematics 2013-09-18 Michael Batanin , Denis-Charles Cisinski , Mark Weber

Recently, a method called the Mutual Information Neural Estimator (MINE) that uses neural networks has been proposed to estimate mutual information and more generally the Kullback-Leibler (KL) divergence between two distributions. The…

Machine Learning · Computer Science 2019-08-20 Kartik Ahuja

The theory of integral, or Fourier-Mukai, transforms between derived categories of sheaves is a well established tool in noncommutative algebraic geometry. General "representation theorems" identify all reasonable linear functors between…

Algebraic Geometry · Mathematics 2021-05-18 David Ben-Zvi , David Nadler , Anatoly Preygel

We consider singular integral operators and maximal singular integral operators with rough kernels on homogeneous groups. We prove certain estimates for the operators that imply $L^p$ boundedness of them by an extrapolation argument under a…

Classical Analysis and ODEs · Mathematics 2010-11-29 Shuichi Sato

This paper introduces a local linear smoother for regression surfaces on the simplex. The estimator solves a least-squares regression problem weighted by a locally adaptive Dirichlet kernel, ensuring good boundary properties. Asymptotic…

Statistics Theory · Mathematics 2025-07-22 Christian Genest , Frédéric Ouimet

A convenient technique for proving kernel theorems for (LF)-spaces (countable inductive limits of Frechet spaces)is developed. The proposed approach is based on introducing a suitable modification of the functor of the completed inductive…

Functional Analysis · Mathematics 2007-05-23 A. G. Smirnov

We prove a new T(1) theorem for multiparameter singular integrals

Classical Analysis and ODEs · Mathematics 2013-02-28 Sandra Pott , Paco Villarroya

We develop a compact version of $T1$ theorem for singular integrals of Zygmund type on $\mathbb{R}^3$. More specifically, if a $(D_{\theta}, \delta_1, \delta_{2, 3})$-Calder\'{o}n-Zygmund operator $T$ associated with Zygmund dilations…

Classical Analysis and ODEs · Mathematics 2025-04-30 Mingming Cao , Jiao Chen , Zhengyang Li , Fanghui Liao , Kôzô Yabuta , Juan Zhang

The discrete kernel method was developed to estimate count data distributions, distinguishing discrete associated kernels based on their asymptotic behaviour. This study investigates the class of discrete asymmetric kernels and their…

Methodology · Statistics 2017-02-07 Tristan Senga Kiessé