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We develop a framework of canonical correlation analysis for distribution-valued functional data within the geometry of Wasserstein spaces. Specifically, we formulate an intrinsic concept of correlation between random distributions, propose…

Methodology · Statistics 2021-06-01 Hang Zhou , Zhenhua Lin , Fang Yao

This text is addressed to mathematicians who are interested in generalized functions and unbounded operators on a Hilbert space. We expose in detail (in a "formal way" - as done by Heisenberg and Pauli - i.e. without mathematical…

Mathematical Physics · Physics 2011-11-10 J. F. Colombeau

This work focuses on the issue of variable selection in functional regression. Unlike most work in this framework, our approach does not select isolated points in the definition domain of the predictors, nor does it rely on the expansion of…

Statistics Theory · Mathematics 2018-03-05 Victor Picheny , Rémi Servien , Nathalie Villa-Vialaneix

We offer new results and new directions in the study of operator-valued kernels and their factorizations. Our approach provides both more explicit realizations and new results, as well as new applications. These include: (i) an explicit…

Quantum Physics · Physics 2025-03-04 Palle E. T. Jorgensen , James Tian

We introduce a notion of completely bounded holomorphic functions defined on the open unit ball of an operator space. We endow the set of these functions with an operator space structure, and in the scalar-valued case we identify an…

Functional Analysis · Mathematics 2024-05-16 Javier Alejandro Chávez-Domínguez , Verónica Dimant

We introduce local iterated function systems and present some of their basic properties. A new class of local attractors of local iterated function systems, namely local fractal functions, is constructed. We derive formulas so that these…

Functional Analysis · Mathematics 2013-09-06 Peter Massopust

We develop nonparametric regression methods for the case when the true regression function is not necessarily smooth. More specifically, our approach is using the fractional Laplacian and is designed to handle the case when the true…

Statistics Theory · Mathematics 2025-06-11 Zhaoyang Shi , Krishnakumar Balasubramanian , Wolfgang Polonik

Recent advances in random linear systems on finite fields have paved the way for the construction of constant-time data structures representing static functions and minimal perfect hash functions using less space with respect to existing…

Data Structures and Algorithms · Computer Science 2016-03-24 Marco Genuzio , Giuseppe Ottaviano , Sebastiano Vigna

A collection of algorithms is described for numerically computing with smooth functions defined on the unit sphere. Functions are approximated to essentially machine precision by using a structure-preserving iterative variant of Gaussian…

Numerical Analysis · Mathematics 2016-04-05 Alex Townsend , Heather Wilber , Grady B. Wright

Snow density estimates as a function of depth are used for understanding climate processes, evaluating water accumulation trends in polar regions, and estimating glacier mass balances. The common and interpretable physically-derived…

Methodology · Statistics 2021-06-22 Philip White , Durban Keeler , Daniel Sheanshang , Summer Rupper

This work is concerned with solving high-dimensional Fokker-Planck equations with the novel perspective that solving the PDE can be reduced to independent instances of density estimation tasks based on the trajectories sampled from its…

Numerical Analysis · Mathematics 2023-12-13 Xun Tang , Lexing Ying

We extend the problem of obtaining an estimator for the finite population mean parameter incorporating complete auxiliary information through calibration estimation in survey sampling but considering a functional data framework. The…

Statistics Theory · Mathematics 2013-02-06 Santiago Gallón , Jean-Michel Loubes , Fabrice Gamboa

Many real-life signals are defined on spherical domains, in particular in geophysics and physics applications. In this work, we tackle the problem of extending the iterative filtering algorithm, developed for the decomposition of…

Numerical Analysis · Mathematics 2023-12-01 Giovanni Barbarino , Roberto Cavassi , Antonio Cicone

We introduce a novel projection depth for data lying in a general Hilbert space, called the regularized projection depth, with a focus on functional data. By regularizing projection directions, the proposed depth does not suffer from the…

Methodology · Statistics 2025-12-24 Filip Bočinec , Stanislav Nagy , Hyemin Yeon

Diffusion generative models have recently been applied to domains where the available data can be seen as a discretization of an underlying function, such as audio signals or time series. However, these models operate directly on the…

Machine Learning · Computer Science 2023-02-28 Gavin Kerrigan , Justin Ley , Padhraic Smyth

We study universal approximation of continuous functionals on compact subsets of products of Hilbert spaces. We prove that any such functional can be uniformly approximated by models that first take finitely many continuous linear…

Machine Learning · Computer Science 2026-02-04 Andrey Krylov , Maksim Penkin

A new classification of real functions and other related real objects defined within a compact interval is proposed. The scope of the classification includes normal real functions and distributions in the sense of Schwartz, referred to…

Mathematical Physics · Physics 2015-07-07 Jorge L. deLyra

Let $H$ be a Hilbert space of entire functions. Let $H'$ be the space of the functions $f(z)/\prod_i(z-z_i)$ where $f$ belongs to $H$ and vanishes at $n$ given complex points $z_i$. We compute a suitable $E$ function for $H'$ when one is…

Functional Analysis · Mathematics 2010-08-04 Jean-François Burnol

The completeness of Gaussians in a Hilbert functional space is established

Classical Analysis and ODEs · Mathematics 2014-06-20 Victor Katsnelson

In this paper, we consider a class of nonconvex and nonsmooth fractional programming problems, that involve the sum of a convex, possibly nonsmooth function composed with a linear operator and a differentiable, possibly nonconvex function…

Optimization and Control · Mathematics 2025-03-18 Radu Ioan Boţ , Guoyin Li , Min Tao