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We introduce kernel density machines (KDM), an agnostic kernel-based framework for learning the Radon-Nikodym derivative (density) between probability measures under minimal assumptions. KDM applies to general measurable spaces and avoids…

Machine Learning · Statistics 2026-03-27 Andrea Della Vecchia , Damir Filipovic , Paul Schneider

We want to approximate general multivariate probability density functions by deterministic sample sets. For optimal sampling, the closeness to the given continuous density has to be assessed. This is a difficult challenge in multivariate…

Systems and Control · Electrical Eng. & Systems 2020-01-01 Uwe D. Hanebeck

This paper considers estimation of a univariate density from an individual numerical sequence. It is assumed that (i) the limiting relative frequencies of the numerical sequence are governed by an unknown density, and (ii) there is a known…

Probability · Mathematics 2008-06-19 Andrew B. Nobel , Gusztav Morvai , Sanjeev R. Kulkarni

If $\mu_1,\mu_2,\dots$ are positive measures on a measurable space $(X,\Sigma)$ and $v_1,v_2, \dots$ are elements of a Banach space ${\mathbb E}$ such that $\sum_{n=1}^\infty \|v_n\| \mu_n(X) < \infty$, then $\omega (S)= \sum_{n=1}^\infty…

Functional Analysis · Mathematics 2019-11-22 Piotr Mikusinski , John Paul Ward

Correlation measure of order $k$ is an important measure of randomness in binary sequences. This measure tries to look for dependence between several shifted version of a sequence. We study the relation between the correlation measure of…

Information Theory · Computer Science 2021-07-27 Zhixiong Chen , Ana I. Gómez , Domingo Gómez-Pérez , Andrew Tirkel

We enquire under which conditions, given two $\sigma$-finite, $\omega$-continuous valuations $\nu$ and $\mu$, $\nu$ has density with respect to $\mu$. The answer is that $\nu$ has to be absolutely continuous with respect to $\mu$, plus a…

Functional Analysis · Mathematics 2023-07-18 Jean Goubault-Larrecq

In this paper we will give a categorical proof of the Radon-Nikodym theorem. We will do this by describing the trivial version of the result on finite probability spaces as a natural isomorphism. We then proceed to Kan extend this…

Category Theory · Mathematics 2023-05-16 Ruben Van Belle

The task of the binary classification problem is to determine which of two distributions has generated a length-$n$ test sequence. The two distributions are unknown; two training sequences of length $N$, one from each distribution, are…

Information Theory · Computer Science 2016-04-18 Dayu Huang , Sean Meyn

Consider a density $f$ on $[0,1]$ that must be estimated from an i.i.d. sample $X_1,...,X_n$ drawn from $f$. In this note, we study binary-tree-based histogram estimates that use recursive splitting of intervals. If the decision to split an…

Statistics Theory · Mathematics 2025-04-24 Luc Devroye , Jad Hamdan

The paper is concerned with one-dimensional two-sided Ornstein-Uhlenbeck type processes with delay or anticipation. We prove existence and uniqueness requiring almost sure boundedness on the left half-axis in case of delay and almost sure…

Probability · Mathematics 2014-12-01 Jörg-Uwe Löbus

We investigate the problem of testing whether a discrete probability distribution over an ordered domain is a histogram on a specified number of bins. One of the most common tools for the succinct approximation of data, $k$-histograms over…

Data Structures and Algorithms · Computer Science 2022-07-15 Clément L. Canonne , Ilias Diakonikolas , Daniel M. Kane , Sihan Liu

We introduce a simple but powerful technique to study processes driven by two or more reinforcement mechanisms in competition. We apply our method to two types of models: to non conservative zero range processes on finite graphs, and to…

Probability · Mathematics 2022-06-30 Dirk Erhard , Guilherme Reis

We derive a closed-form expression for the orthogonal polynomials associated with the general lognormal density. The result can be utilized to construct easily computable approximations for probability density function of a product of…

Information Theory · Computer Science 2016-11-17 Zhong Zheng , Lu Wei , Jyri Hämäläinen , Olav Tirkkonen

Two classes of topological spaces are introduced on which every probability Radon measure possesses a uniformly distributed sequence or a uniformly tight uniformly distributed sequence. It is shown that these classes are stable under…

General Topology · Mathematics 2007-08-28 V. I. Bogachev , M. N. Lukintsova

This paper studies quantitative deviation bounds for statistical ensembles evolving under the one-parameter flow of a nearly integrable Hamiltonian system. Combining Nekhoroshev-type stability estimates with phase-mixing arguments, we…

Dynamical Systems · Mathematics 2026-02-23 Xinyu Liu , Yong Li

Histograms are convenient non-parametric density estimators, which continue to be used ubiquitously. Summary quantities estimated from histogram-based probability density models depend on the choice of the number of bins. We introduce a…

Data Analysis, Statistics and Probability · Physics 2013-09-17 Kevin H. Knuth

We show from a categorical point of view that probability measures on certain measurable or topological spaces arise canonically as the extension of probability distributions on countable sets. We do this by constructing probability monads…

Category Theory · Mathematics 2022-06-23 Ruben Van Belle

The set of diagonals of real symmetric matrices of given non negative spectrum is endowed with a measure which is obtained by the push forward of the Haar measure of the real orthogonal group.\\ We prove that the Radon Nicodym derivation of…

Representation Theory · Mathematics 2015-05-26 Avital Frumkin , Assaf Goldberger

We introduce and investigate superdensity and the density degree of sets with respect to a Radon measure on ${\mathbf R}^n$. Some applications are provided. In particular we prove a result on the approximability of a set by closed subsets…

Functional Analysis · Mathematics 2024-07-12 Silvano Delladio

We study the Lp-integrated risk of some classical estimators of the density, when the observations are drawn from a strictly stationary sequence. The results apply to a large class of sequences, which can be non-mixing in the sense of…

Statistics Theory · Mathematics 2016-05-18 Jérôme Dedecker , Florence Merlevède