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We describe five types of results concerning information and concentration of discrete random variables, and relationships between them, motivated by their counterparts in the continuous case. The results we consider are information…

Probability · Mathematics 2017-04-25 Oliver Johnson

Given a network of fixed size $n$ and an initial distribution of data, we derive sufficient connectivity conditions on a sequence of time-varying digraphs for (a) data collection and (b) data dissemination, within at most $(n-1)$…

Systems and Control · Computer Science 2016-05-03 Kevin Topley

A novel, non-trivial, probabilistic upper bound on the entropy of an unknown one-dimensional distribution, given the support of the distribution and a sample from that distribution, is presented. No knowledge beyond the support of the…

Information Theory · Computer Science 2007-07-13 Joseph DeStefano , Erik Learned-Miller

We generalize the well-known Coupon Collector Problem (CCP) in combinatorics. Our problem is to find the minimum and expected number of draws, with replacement, required to recover $n$ distinctly labeled coupons, with each draw consisting…

Discrete Mathematics · Computer Science 2025-07-22 Andrew Tan , Oriel Limor , Daniella Bar-Lev , Ryan Gabrys , Zohar Yakhini , Paul H. Siegel

Motivated by a problem in the theory of randomized search heuristics, we give a very precise analysis for the coupon collector problem where the collector starts with a random set of coupons (chosen uniformly from all sets). We show that…

Discrete Mathematics · Computer Science 2017-08-01 Benjamin Doerr , Carola Doerr

Determining the strength of non-linear statistical dependencies between two variables is a crucial matter in many research fields. The established measure for quantifying such relations is the mutual information. However, estimating mutual…

Data Analysis, Statistics and Probability · Physics 2019-07-24 Damián G. Hernández , Inés Samengo

Most work on supervised learning research has focused on marginal predictions. In decision problems, joint predictive distributions are essential for good performance. Previous work has developed methods for assessing low-order predictive…

Machine Learning · Statistics 2022-03-01 Ian Osband , Zheng Wen , Seyed Mohammad Asghari , Vikranth Dwaracherla , Xiuyuan Lu , Benjamin Van Roy

In applied probability, the normal approximation is often used for the distribution of data with assumed additive structure. This tradition is based on the central limit theorem for sums of (independent) random variables. However, it is…

Probability · Mathematics 2020-10-27 Alexandra Dorofeeva , Victor Korolev , Alexander Zeifman

We formulate the statistics of the discrete multicomponent fragmentation event using a methodology borrowed from statistical mechanics. We generate the ensemble of all feasible distributions that can be formed when a single integer…

Statistical Mechanics · Physics 2020-07-03 Themis Matsoukas

Correlations in music that exist within its waveform are studied. Monophonic wave files of random music are generated and the probability distribution function of time interval between large signal values is analyzed. A power law behavior…

Adaptation and Self-Organizing Systems · Physics 2008-11-25 Vishnu Sreekumar , Mahendra K. Verma , Gaurav Narain , Venkatesh K. S

We consider the model of random sequential adsorption, with depositing objects, as well as those already at the surface, decreasing in size according to a specified time dependence, from a larger initial value to a finite value in the large…

Mathematical Physics · Physics 2010-10-12 Oleksandr Gromenko , Vladimir Privman

The general relationship between an arbitrary frequency distribution and the expectation value of the frequency distributions of its samples is discussed. A wide set of measurable quantities ("invariant moments") whose expectation value…

Data Analysis, Statistics and Probability · Physics 2015-06-15 Paolo Rossi

Statistical system models provide the basis for the examination of various sorts of distributions. Classification distributions are a very common and versatile form of statistics in e.g. real economic, social, and IT systems. The…

Computation · Statistics 2019-12-20 Uwe Petersohn , Thomas Dedek , Sandra Zimmer , Hans Biskupski

Sampling algorithms, hypergraph degree sequences, and polytopes play a crucial role in statistical analysis of network data. This article offers a brief overview of open problems in this area of discrete mathematics from the point of view…

Discrete Mathematics · Computer Science 2016-01-11 Sonja Petrović

We register a random sequence which has the following properties: it has three segments being the homogeneous Markov processes. Each segment has his own one step transition probability law and the length of the segment is unknown and…

Probability · Mathematics 2011-11-21 Krzysztof Szajowski

Recent results in compressed sensing showed that the optimal subsampling strategy should take into account the sparsity pattern of the signal at hand. This oracle-like knowledge, even though desirable, nevertheless remains elusive in most…

Information Theory · Computer Science 2023-06-28 Simon Ruetz

The aim of the present work is to show that the results obtained earlier on the approximation of distributions of sums of independent terms by the accompanying compound Poisson laws may be interpreted as rather sharp quantitative estimates…

Probability · Mathematics 2022-08-04 Friedrich Götze , Andrei Yu. Zaitsev

We propose a new setting for testing properties of distributions while receiving samples from several distributions, but few samples per distribution. Given samples from $s$ distributions, $p_1, p_2, \ldots, p_s$, we design testers for the…

Data Structures and Algorithms · Computer Science 2019-11-19 Maryam Aliakbarpour , Sandeep Silwal

It is often necessary to make sampling-based statistical inference about many probability distributions in parallel. Given a finite computational resource, this article addresses how to optimally divide sampling effort between the samplers…

Methodology · Statistics 2015-02-18 Nicholas Heard , Melissa Turcotte

Given an $N$-dimensional subspace $X$ of $L_p([0,1])$, we consider the problem of choosing $M$-sampling points which may be used to discretely approximate the $L_p$ norm on the subspace. We are particularly interested in knowing when the…

Functional Analysis · Mathematics 2022-02-08 Daniel Freeman , Dorsa Ghoreishi