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This paper considers model spaces in an $H_p$ setting. The existence of unbounded functions and the characterisation of maximal functions in a model space are studied, and decomposition results for Toeplitz kernels, in terms of model…

Functional Analysis · Mathematics 2015-07-22 M. C. Câmara , M. T. Malheiro , J. R. Partington

This paper systematically studies the behavior of the leading eigenvectors for independent edge undirected random graphs generated from a general latent position model whose link function is possibly infinite rank and also possibly…

Statistics Theory · Mathematics 2025-01-28 Minh Tang , Joshua R. Cape

In this paper, we develop asymptotic theories for a class of latent variable models for large-scale multi-relational networks. In particular, we establish consistency results and asymptotic error bounds for the (penalized) maximum…

Statistics Theory · Mathematics 2020-09-01 Zhi Wang , Xueying Tang , Jingchen Liu

This paper shows that the logarithm of the epsilon-error capacity (average error probability) for n uses of a discrete memoryless channel is upper bounded by the normal approximation plus a third-order term that does not exceed 1/2 log n +…

Information Theory · Computer Science 2013-10-25 Marco Tomamichel , Vincent Y. F. Tan

In this paper we investigate the problem of estimating the regression function in models with correlated observations. The data is obtained from several experimental units each of them forms a time series. We propose a new estimator based…

Statistics Theory · Mathematics 2019-06-13 Djihad Benelmadani , Karim Benhenni , Sana Louhichi

The structure of data organization is widely recognized as having a substantial influence on the efficacy of machine learning algorithms, particularly in binary classification tasks. Our research provides a theoretical framework suggesting…

Machine Learning · Computer Science 2024-07-15 Fei Jing , Zi-Ke Zhang , Yi-Cheng Zhang , Qingpeng Zhang

The necessity of a Maximum Principle arises naturally when one is interested in the study of qualitative properties of solutions to partial differential equations. In general, to ensure the validity of these kind of principles one has to…

Analysis of PDEs · Mathematics 2023-10-04 Andrea Bisterzo

High-dimensional functional data have become increasingly prevalent in modern applications such as high-frequency financial data and neuroimaging data analysis. We investigate a class of high-dimensional linear regression models, where each…

Methodology · Statistics 2025-11-06 Xingche Guo , Yehua Li , Tailen Hsing

We study Berezin-Toeplitz quantization of complex projective spaces $\mathbb{CP}^{d-1}$ and obtain full asymptotic expansions of the Berezin transformation and of products of Toeplitz operators. In each case, the remainder is controlled by…

Mathematical Physics · Physics 2025-08-28 Tommaso Aschieri , Błażej Ruba , Jan Philip Solovej

We perform a study on kernel regression for large-dimensional data (where the sample size $n$ is polynomially depending on the dimension $d$ of the samples, i.e., $n\asymp d^{\gamma}$ for some $\gamma >0$ ). We first build a general tool to…

Machine Learning · Statistics 2024-07-01 Weihao Lu , Haobo Zhang , Yicheng Li , Manyun Xu , Qian Lin

This paper addresses the problem of approximating an unknown function from point evaluations. When obtaining these point evaluations is costly, minimising the required sample size becomes crucial, and it is unreasonable to reserve a…

Numerical Analysis · Mathematics 2025-11-06 Nando Hegemann , Anthony Nouy , Philipp Trunschke

Explicit representations of the eigenvalues of the peridynamic operator have been recently derived in [5]. These representations are given in terms of generalized hypergeometric functions. Asymptotic analysis of the hypergeometric functions…

Mathematical Physics · Physics 2023-08-21 Bacim Alali , Nathan Albin , Thinh Dang

In many contexts one encounters Hermitian operators $M$ on a Hilbert space whose dimension is so large that it is impossible to write down all matrix entries in an orthonormal basis. How does one determine whether such $M$ is positive…

Algebraic Geometry · Mathematics 2020-04-17 Gemma de las Cuevas , Tobias Fritz , Tim Netzer

Let ${\mbox{$\mbox{\boldmath $f$}$}}$ be a square-integrable, zero-mean, random vector with observable realizations in a Hilbert space $H$, and let ${\mbox{$\mbox{\boldmath $g$}$}}$ be an associated square-integrable, zero-mean, random…

Statistics Theory · Mathematics 2020-08-31 Phil Howlett , Anatoli Totokhti

We provide quantitative bounds measuring the $L^2$ difference in function space between the trajectory of a finite-width network trained on finitely many samples from the idealized kernel dynamics of infinite width and infinite data. An…

Machine Learning · Statistics 2022-10-18 Benjamin Bowman , Guido Montufar

The primary objective of this paper is to establish the Ahlfors regularity of minimizers of set functions that satisfy a suitable maxitive condition on disjoint unions of sets. Our analysis focuses on minimizers within continua of the plane…

Optimization and Control · Mathematics 2024-09-04 Davide Zucco

In this paper we study some questions about the continuity of classical and fractional maximal operators in the Sobolev space $W^{1,1}$, in both continuous and discrete setting, giving a positive answer to two questions posed recently, one…

Classical Analysis and ODEs · Mathematics 2017-10-11 José Madrid

Consider a Hermitian operator $A$ acting on a complex Hilbert space of dimension $2^n$. We show that when $A$ has small degree in the Pauli expansion, or in other words, $A$ is a local $n$-qubit Hamiltonian, its operator norm can be…

Quantum Physics · Physics 2026-04-10 Lars Becker , Joseph Slote , Alexander Volberg , Haonan Zhang

This paper investigates optimal error bounds and convergence rates for general Mann iterations for computing fixed-points of non-expansive maps. We look for iterations that achieve the smallest fixed-point residual after $n$ steps, by…

Optimization and Control · Mathematics 2022-05-13 Juan Pablo Contreras , Roberto Cominetti

Generalizing previous work of Iwaniec, Luo, and Sarnak (2000), we use information from one-level density theorems to estimate the proportion of non-vanishing of $L$-functions in a family at a low-lying height on the critical line (measured…

Number Theory · Mathematics 2022-10-17 Emanuel Carneiro , Andrés Chirre , Micah B. Milinovich
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