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Many functionals of interest in statistics and machine learning can be written as minimizers of expected loss functions. Such functionals are called $M$-estimands, and can be estimated by $M$-estimators -- minimizers of empirical average…

Statistics Theory · Mathematics 2024-11-27 Arunav Bhowmick , Arun Kumar Kuchibhotla

We study a novel class of affine invariant and consistent tests for normality in any dimension. The tests are based on a characterization of the standard $d$-variate normal distribution as the unique solution of an initial value problem of…

Methodology · Statistics 2019-09-30 Philip Dörr , Bruno Ebner , Norbert Henze

We study the fixed point for a non-linear transformation in the set of Hausdorff moment sequences, defined by the formula: $T((a_n))_n=1/(a_0+... +a_n)$. We determine the corresponding measure $\mu$, which has an increasing and convex…

Classical Analysis and ODEs · Mathematics 2016-08-14 Christian Berg , Antonio J. Durán

We consider a random walk $S_k$ with i.i.d. steps on a compact group equipped with a bi-invariant metric. We prove quantitative ergodic theorems for the sum $\sum_{k=1}^N f(S_k)$ with H\"older continuous test functions $f$, including the…

Probability · Mathematics 2022-09-27 Bence Borda

We propose a function-valued evaluation metric for generative models based on the relative density ratio (RDR) designed to characterize distributional differences between real and generated samples. As an evaluation metric, the RDR function…

Methodology · Statistics 2025-12-29 Yuliang Xu , Yun Wei , Li Ma

A generalized divergence theorem is established allowing for domains with inner boundaries. The normal trace of a rough integrand is not a Radon measure; rather, the boundary integral is expressed via a surface functional continuous with…

Analysis of PDEs · Mathematics 2025-10-29 Thomas Ruf

We prove general results about separation and weak$^\#$-convergence of boundedly finite measures on separable metric spaces and Souslin spaces. More precisely, we consider an algebra of bounded real-valued, or more generally a $*$-algebra…

Probability · Mathematics 2016-09-12 Wolfgang Löhr , Thomas Rippl

We consider a new class $\boldsymbol{Q}$ of distribution functions $F$ that have the property of rational-infinite divisibility: there exist some infinitely divisible distribution functions $F_1$ and $F_2$ such that $F_1=F*F_2$. A…

Probability · Mathematics 2024-12-30 A. A. Khartov

In a previous article, we extended the notion of ergodic optimization to the setting of C*-dynamical systems of countable discrete groups. Among the key results of that paper was that given an action $G \stackrel{\Xi}{\curvearrowright}…

Operator Algebras · Mathematics 2021-09-30 Aidan Young

Information divergence functions play a critical role in statistics and information theory. In this paper we show that a non-parametric f-divergence measure can be used to provide improved bounds on the minimum binary classification…

Information Theory · Computer Science 2015-02-11 Visar Berisha , Alan Wisler , Alfred O. Hero , Andreas Spanias

We introduce a theory of probability in $\lambda$-rings designed to efficiently describe random variables valued in multisets of complex numbers, varieties over a field, or other similar enriched settings. A key role is played by the…

Number Theory · Mathematics 2025-06-10 Sean Howe

We introduce and study a log discrepancy function on the space of semivaluations centered on an integral noetherian scheme of positive characteristic. Our definition shares many properties with the analogue in characteristic zero; we prove…

Algebraic Geometry · Mathematics 2021-02-16 Eric Canton

To understand the sample-to-sample fluctuations in disorder-generated multifractal patterns we investigate analytically as well as numerically the statistics of high values of the simplest model - the ideal periodic $1/f$ Gaussian noise. By…

Statistical Mechanics · Physics 2015-06-05 Yan V. Fyodorov , Pierre Le Doussal , Alberto Rosso

Divergence functions are measures of distance or dissimilarity between probability distributions that serve various purposes in statistics and applications. We propose decompositions of Wasserstein and Cram\'er distances$-$which compare two…

Methodology · Statistics 2025-08-08 Johannes Resin , Daniel Wolffram , Johannes Bracher , Timo Dimitriadis

We propose a study of a distribution registration model for general deformation functions. In this framework, we provide estimators of the deformations as well as a goodness of fit test of the model. For this, we consider a criterion which…

Statistics Theory · Mathematics 2015-10-02 Eustasio Del Barrio , Hélène Lescornel , Jean-Michel Loubes

We characterize the symmetric distributions that can be (approximately) generated by shallow Boolean circuits. More precisely, let $f\colon \{0,1\}^m \to \{0,1\}^n$ be a Boolean function where each output bit depends on at most $d$ input…

Computational Complexity · Computer Science 2025-11-19 Daniel M. Kane , Anthony Ostuni , Kewen Wu

We prove that every nonnegative continuous real-valued function on a given compact metric space is the uniform limit of some increasing sequence of nonnegative simple functions being linear combinations of indicators of open sets; here the…

General Mathematics · Mathematics 2020-10-21 Yu-Lin Chou

We develop a framework for function classes generated by parametric ridge kernels: one-dimensional kernels composed with affine projections and averaged over a parameter measure. The induced kernels are positive definite, and the resulting…

Functional Analysis · Mathematics 2025-08-26 James Tian

At the present time reliably established that probability density functions of gene expression of microarray experiments possess a number of universal properties. First of all these distributions have power asymptotic and secondly the shape…

Statistics Theory · Mathematics 2015-06-08 Viacheslav Saenko , Yurij Saenko

Let $f:\mathbb{R} \to \mathbb{R}$ be a stationary centered Gaussian process. For any $R>0$, let $\nu_R$ denote the counting measure of $\{x \in \mathbb{R} \mid f(Rx)=0\}$. In this paper, we study the large $R$ asymptotic distribution of…

Probability · Mathematics 2021-05-19 Michele Ancona , Thomas Letendre
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