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In this paper we will look at the distribution with which passwords are chosen. Zipf's Law is commonly observed in lists of chosen words. Using password lists from four different on-line sources, we will investigate if Zipf's law is a good…

Cryptography and Security · Computer Science 2015-09-02 David Malone , Kevin Maher

We study coverage processes in which each draw reveals a subset of $[n]$, and the goal is to determine the expected number of draws until all items are seen at least once. A classical example is the Coupon Collector's Problem, where each…

Information Theory · Computer Science 2025-10-30 Yitzchak Grunbaum , Eitan Yaakobi

We prove that, in the coupon collector's problem, the point processes given by the times of $r$-th arrivals for coupons of each type, centered and normalized in a proper way, converge toward a non-homogeneous Poisson point process. This…

Probability · Mathematics 2019-09-16 Andrii Ilienko

We explore a probabilistic model of an artistic text: words of the text are chosen independently of each other in accordance with a discrete probability distribution on an infinite dictionary. The words are enumerated 1, 2, $\ldots$, and…

Statistics Theory · Mathematics 2019-05-02 Mikhail Chebunin , Artyom Kovalevskii

Many machine learning tasks, such as learning with invariance and policy evaluation in reinforcement learning, can be characterized as problems of learning from conditional distributions. In such problems, each sample $x$ itself is…

Machine Learning · Computer Science 2017-01-03 Bo Dai , Niao He , Yunpeng Pan , Byron Boots , Le Song

We consider the problem of choosing the best of $n$ samples, out of a large random pool, when the sampling of each member is associated with a certain cost. The quality (worth) of the best sample clearly increases with $n$, but so do the…

Statistics Theory · Mathematics 2015-06-16 Joseph D. Skufca , Daniel ben-Avraham

Given samples from an unknown distribution $p$, is it possible to distinguish whether $p$ belongs to some class of distributions $\mathcal{C}$ versus $p$ being far from every distribution in $\mathcal{C}$? This fundamental question has…

Data Structures and Algorithms · Computer Science 2015-12-09 Jayadev Acharya , Constantinos Daskalakis , Gautam Kamath

This paper formalizes a latent variable inference problem we call {\em supervised pattern discovery}, the goal of which is to find sets of observations that belong to a single ``pattern.'' We discuss two versions of the problem and prove…

Machine Learning · Statistics 2014-02-10 Jonathan H. Huggins , Cynthia Rudin

We study the problem of generating a random variate $X$ from a finite discrete probability distribution $P$ using an entropy source of independent fair coin flips. A classic result from Knuth and Yao shows that the optimal expected number…

Data Structures and Algorithms · Computer Science 2026-04-28 Thomas L. Draper , Feras A. Saad

The takeoff point for this paper is the voluminous body of literature addressing recursive betting games with expected logarithmic growth of wealth being the performance criterion. Whereas almost all existing papers involve use of linear…

Optimization and Control · Mathematics 2024-01-17 Anton V. Proskurnikov , B. Ross Barmish

A random vector $X$ with representation $X=\sum_{j\geq0}A_jZ_j$ is considered. Here, $(Z_j)$ is a sequence of independent and identically distributed random vectors and $(A_j)$ is a sequence of random matrices, `predictable' with respect to…

Probability · Mathematics 2009-09-29 Henrik Hult , Gennady Samorodnitsky

We address the role of multiplicative stochastic processes in modeling the occurrence of power-law city size distributions. As an explanation of the result of Zipf's rank analysis, Simon's model is presented in a mathematically elementary…

Physics and Society · Physics 2007-05-23 Damian H. Zanette

In the "correlated sampling" problem, two players are given probability distributions $P$ and $Q$, respectively, over the same finite set, with access to shared randomness. Without any communication, the two players are each required to…

Computational Complexity · Computer Science 2020-11-24 Mohammad Bavarian , Badih Ghazi , Elad Haramaty , Pritish Kamath , Ronald L. Rivest , Madhu Sudan

We investigate a problem in which each member of a group of learners is trained separately to solve the same classification task. Each learner has access to a training dataset (possibly with overlap across learners) but each trained…

Machine Learning · Computer Science 2020-03-03 Mahmoud Albardan , John Klein , Olivier Colot

Here we sketch a new derivation of Zipf's law for word frequencies based on optimal coding. The structure of the derivation is reminiscent of Mandelbrot's random typing model but it has multiple advantages over random typing: (1) it starts…

Computation and Language · Computer Science 2020-09-24 Ramon Ferrer-i-Cancho

In this paper, we prove that the numerical-semigroup-gap counting problem is #NP-complete as a main theorem. A numerical semigroup is an additive semigroup over the set of all nonnegative integers. A gap of a numerical semigroup is defined…

Computational Complexity · Computer Science 2017-01-05 Shunichi Matsubara

The problem of compression in standard information theory consists of assigning codes as short as possible to numbers. Here we consider the problem of optimal coding -- under an arbitrary coding scheme -- and show that it predicts Zipf's…

Computation and Language · Computer Science 2020-09-24 Ramon Ferrer-i-Cancho , Christian Bentz , Caio Seguin

We treat a random number generation from an i.i.d. probability distribution of $P$ to that of $Q$. When $Q$ or $P$ is a uniform distribution, the problems have been well-known as the uniform random number generation and the resolvability…

Information Theory · Computer Science 2013-03-05 Wataru Kumagai , Masahito Hayashi

Zipf's law, which states that the probability of an observation is inversely proportional to its rank, has been observed in many domains. While there are models that explain Zipf's law in each of them, those explanations are typically…

Neurons and Cognition · Quantitative Biology 2016-07-06 Laurence Aitchison , Nicola Corradi , Peter E. Latham

In this paper we consider a scenario where there are several algorithms for solving a given problem. Each algorithm is associated with a probability of success and a cost, and there is also a penalty for failing to solve the problem. The…

Data Structures and Algorithms · Computer Science 2020-08-11 Shlomo Moran , Irad Yavneh
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