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A new formalism is presented for finding equilibrium distribution functions for axisymmetric systems. The formalism, obtainded by using the concept of fractional derivatives, generalizes the methods of Fricke (1952), Kalnajs (1972) and…

Astrophysics · Physics 2009-06-14 Juan F. Pedraza , Javier Ramos-Caro , Guillermo A. Gonzalez

Sequential probability assignment and universal compression go hand in hand. We propose sequential probability assignment for non-binary (and large alphabet) sequences with empirical distributions whose parameters are known to be bounded…

Information Theory · Computer Science 2021-02-09 Michael Drmota , Gil Shamir , Wojciech Szpankowski

The one-dimensional Dickman distribution arises in various stochastic models across number theory, combinatorics, physics, and biology. Recently, a definition of the multidimensional Dickman distribution has appeared in the literature,…

Probability · Mathematics 2026-04-30 Anastasiia S. Kovtun , Nikolai N. Leonenko , Andrey Pepelyshev

In this article we introduce associative Look-Up Tables. With their help, pseudo sums are correctly determined. The set of limit distributions in a pseudo-summation scheme of i.i.d. random variables is described. Also, two special cases…

Probability · Mathematics 2023-06-02 Ivan Alexeev , Ignat Melnikov , Artem Uglovski

Similarity functions measure how comparable pairs of elements are, and play a key role in a wide variety of applications, e.g., notions of Individual Fairness abiding by the seminal paradigm of Dwork et al., as well as Clustering problems.…

Machine Learning · Computer Science 2023-10-24 Leonidas Tsepenekas , Ivan Brugere , Freddy Lecue , Daniele Magazzeni

In this paper we provide a systematic exposition of basic properties of integrated distribution and quantile functions. We define these transforms in such a way that they characterize any probability distribution on the real line and are…

Probability · Mathematics 2018-01-04 Alexander A. Gushchin , Dmitriy A. Borzykh

We analyse the complexity of environments according to the policies that need to be used to achieve high performance. The performance results for a population of policies leads to a distribution that is examined in terms of policy…

Artificial Intelligence · Computer Science 2013-02-11 Jose Hernandez-Orallo

The general relationship between an arbitrary frequency distribution and the expectation value of the frequency distributions of its samples is esablished. A set of combinations of expectation values whose value does not in general depend…

Data Analysis, Statistics and Probability · Physics 2012-10-05 Paolo Rossi

A new bound for the remainder term in the Taylor expansion of the complex exponent $e^{ix}$, $x\in\R$, is proved yielding precise moment-type estimates of the accuracy of the approximation of the characteristic function (the…

Probability · Mathematics 2018-04-02 Irina Shevtsova

In this work, we attempt to refine the classic asymptotic formulae to describe the probability distribution of likelihood-ratio statistical tests. The idea is to split the probability distribution function into two parts. One part is…

Data Analysis, Statistics and Probability · Physics 2025-07-29 Li-Gang Xia , Yan Zhang

Numerous entropy-type characteristics (functionals) generalizing R\'enyi entropy are widely used in mathematical statistics, physics, information theory, and signal processing for characterizing uncertainty in probability distributions and…

Statistics Theory · Mathematics 2011-03-28 David Källberg , Nikolaj Leonenko , Oleg Seleznjev

We study power-mixture type functional equations in terms of Laplace-Stieltjes transforms of probability distributions. These equations arise when studying distributional equations of the type Z = X + TZ, where T is a known random variable,…

Probability · Mathematics 2020-09-22 Chin-Yuan Hu , Gwo Dong Lin , Jordan M. Stoyanov

A pattern of a sequence is a sequence of integer indices with each index describing the order of first occurrence of the respective symbol in the original sequence. In a recent paper, tight general bounds on the block entropy of patterns of…

Information Theory · Computer Science 2007-11-15 Gil I. Shamir

We consider the distribution of the sum and the maximum of a collection of independent exponentially distributed random variables. The focus is laid on the explicit form of the density functions (pdf) of non-i.i.d. sequences. Those are…

Probability · Mathematics 2013-07-16 Markus Bibinger

We consider three classes of linear differential equations on distribution functions, with a fractional order $\alpha\in [0,1].$ The integer case $\alpha =1$ corresponds to the three classical extreme families. In general, we show that…

Probability · Mathematics 2019-08-05 Lotfi Boudabsa , Thomas Simon , Pierre Vallois

We consider the problem of approximating two, possibly unrelated probability distributions from a single complex-valued function $\psi$ and its Fourier transform. We show that this problem always has a solution within a specified degree of…

Mathematical Physics · Physics 2011-01-12 W. D. Flanders , G. Japaridze

A predictive distribution over a sequence of $N+1$ events is said to be "frequency mimicking" whenever the probability for the final event conditioned on the outcome of the first $N$ events equals the relative frequency of successes among…

Methodology · Statistics 2019-09-06 Frank Lad , Giuseppe Sanfilippo

The study of convolution powers of a finitely supported probability distribution $\phi$ on the $d$-dimensional square lattice is central to random walk theory. For instance, the $n$th convolution power $\phi^{(n)}$ is the distribution of…

Classical Analysis and ODEs · Mathematics 2016-03-25 Evan Randles , Laurent Saloff-Coste

We give necessary and sufficient criteria for a distribution to be smooth or uniformly H\"{o}lder continuous in terms of approximation sequences by smooth functions; in particular, in terms of those arising as regularizations…

Functional Analysis · Mathematics 2013-05-02 Stevan Pilipovic , Dimitris Scarpalezos , Jasson Vindas

Deep neural networks trained in an end-to-end manner are proven to be efficient in a wide range of machine learning tasks. However, there is one drawback of end-to-end learning: The learned features and information are implicitly…

Machine Learning · Computer Science 2024-06-07 Canlin Zhang , Xiuwen Liu
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