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Let $\mathrm{Lip}_0(M)$ be the space of Lipschitz functions on a complete metric space $(M,d)$ that vanish at a point $0\in M$. We investigate its dual $\mathrm{Lip}_0(M)^*$ using the de Leeuw transform, which allows representing each…

Functional Analysis · Mathematics 2026-03-17 Ramón J. Aliaga , E. Pernecká , Richard J. Smith

In this article, we construct semiparametrically efficient estimators of linear functionals of a probability measure in the presence of side information using an easy empirical likelihood approach. We use estimated constraint functions and…

Methodology · Statistics 2023-03-01 Shan Wang , Hanxiang Peng

We establish strong dynamical localization for a class of multi-particle Anderson models in a Euclidean space with an alloy-type random potential and a sub-exponentially decaying interaction of infinite range. For the first time in the…

Mathematical Physics · Physics 2014-07-18 Victor Chulaevsky

In many applications such as web-based search, document summarization, facility location and other applications, the results are preferable to be both representative and diversified subsets of documents. The goal of this study is to select…

Machine Learning · Computer Science 2015-11-10 Sepehr Abbasi Zadeh , Mehrdad Ghadiri

An RD-space ${\mathcal X}$ is a space of homogeneous type in the sense of Coifman and Weiss with the additional property that a reverse doubling condition holds in ${\mathcal X}$. Let $\rho$ be an admissible function on RD-space ${\mathcal…

Functional Analysis · Mathematics 2009-11-07 Dachun Yang , Dongyong Yang , Yuan Zhou

Following ideas of Caffarelli and Silvestre in~\cite{CS}, and using recent progress in hyperbolic fillings, we define fractional $p$-Laplacians $(-\Delta_p)^\theta$ with $0<\theta<1$ on any compact, doubling metric measure space…

Analysis of PDEs · Mathematics 2022-04-04 Luca Capogna , Josh Kline , Riikka Korte , Nageswari Shanmugalingam , Marie Snipes

The Typical Medium Theory provides conceptually the simplest order parameter description of Anderson localization by self-consistently calculating the geometrically-averaged (typical) local density of states (LDOS). Here we show how spatial…

Disordered Systems and Neural Networks · Physics 2016-08-08 Samiyeh Mahmoudian , Vladimir Dobrosavljević

The maximally localized Wannier functions play a very important role in the study of chemical bonding, ballistic transport and strongly-correlated system, etc. A significant development in this branch was made in 1997 and conjectured that…

Materials Science · Physics 2014-07-28 Sangryol Ri , Suil Ri

Asymptotic methods for hypothesis testing in high-dimensional data usually require the dimension of the observations to increase to infinity, often with an additional condition on its rate of increase compared to the sample size. On the…

Statistics Theory · Mathematics 2024-03-26 Joydeep Chowdhury , Subhajit Dutta , Marc G. Genton

Maximally-localized Wannier functions are quantum wavefunctions resembling atomic orbitals that are used to describe electrons in condensed matter. Since their introduction in 1997, these functions have become ubiquitous in ab initio…

Computational Physics · Physics 2026-04-09 Sabyasachi Tiwari , Bruno Cucco , Viet-Anh Ha , Feliciano Giustino

The $L^{p,\infty}$ quasi-norm of functions on a measure space can be characterized in terms of their pairing with normalized characteristic functions. We generalize this result to the case of the outer $L^{p,\infty}$ quasi-norms for…

Classical Analysis and ODEs · Mathematics 2023-03-03 Marco Fraccaroli

The primary objective of the present paper is to develop the theory of quantization dimension of an invariant measure associated with an iterated function system consisting of finite number of contractive infinitesimal similitudes in a…

Dynamical Systems · Mathematics 2020-05-19 Mrinal K. Roychowdhury , S. Verma

Let $\nu\in M^1([0,\infty[)$ be a fixed probability measure. For each dimension $p\in \mathbb{N}$, let $(X_n^{p})_{n\geq1}$ be i.i.d. $\mathbb{R}^p$-valued random variables with radially symmetric distributions and radial distribution…

Probability · Mathematics 2019-02-20 Waldemar Grundmann

We study the localization of wave functions for one-dimensional Schr\"odinger Hamiltonians with random potentials $V(x)$ with short range correlations and large local fluctuations such that $\int\D{x} \smean{V(x)V(0)}=\infty$. A random…

Disordered Systems and Neural Networks · Physics 2008-10-27 Tom Bienaime , Christophe Texier

We prove a quantified Tauberian theorem for functions under a new kind of Tauberian condition. In this condition we assume in particular that the Laplace transform of the considered function extends to a domain to the left of the imaginary…

Functional Analysis · Mathematics 2017-05-11 Reinhard Stahn

We consider improvements of Dirichlet's Theorem on space of matrices $M_{m,n}(R)$. It is shown that for a certain class of fractals $K\subset [0,1]^{mn}\subset M_{m,n}(R)$ of local maximal dimension Dirichlet's Theorem cannot be improved…

Dynamical Systems · Mathematics 2009-05-11 Ronggang Shi

Let $({\mathcal X}, d, \mu)$ be a metric measure space and satisfy the so-called upper doubling condition and the geometrically doubling condition. In this paper, the authors introduce the space ${\mathop\mathrm{RBLO}}(\mu)$ and prove that…

Classical Analysis and ODEs · Mathematics 2010-12-20 Haibo Lin , Dachun Yang

The Fourier transforms of the products of two respectively three solutions of the free Schroedinger equation in one space dimension are estimated in mixed and, in the first case weighted, L^p - norms. Inserted into an appropriate variant of…

Analysis of PDEs · Mathematics 2007-05-23 Axel Gruenrock

The classification loss functions used in deep neural network classifiers can be grouped into two categories based on maximizing the margin in either Euclidean or angular spaces. Euclidean distances between sample vectors are used during…

Computer Vision and Pattern Recognition · Computer Science 2022-12-23 Hakan Cevikalp , Hasan Saribas

The challenge of approximating functions in infinite-dimensional spaces from finite samples is widely regarded as formidable. We delve into the challenging problem of the numerical approximation of Sobolev-smooth functions defined on…

Optimization and Control · Mathematics 2024-10-11 Massimo Fornasier , Pascal Heid , Giacomo Enrico Sodini
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