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The Curie-Weiss model, originally used to study phase transitions in statistical mechanics, has been adapted to model phenomena in social sciences where many agents interact with each other. Reconstructing the probability measure of a…

Statistics Theory · Mathematics 2025-07-24 Miguel Ballesteros , Ivan Naumkin , Gabor Toth

Approximation algorithms for classical constraint satisfaction problems are one of the main research areas in theoretical computer science. Here we define a natural approximation version of the QMA-complete local Hamiltonian problem and…

Quantum Physics · Physics 2016-10-25 Sevag Gharibian , Julia Kempe

We study the distribution regression problem assuming the distribution of distributions has a doubling measure larger than one. First, we explore the geometry of any distributions that has doubling measure larger than one and build a small…

Machine Learning · Computer Science 2022-03-02 Ilqar Ramazanli

Estimating the density of a distribution from its samples is a fundamental problem in statistics. Hypothesis selection addresses the setting where, in addition to a sample set, we are given $n$ candidate distributions -- referred to as…

Data Structures and Algorithms · Computer Science 2025-10-23 Maryam Aliakbarpour , Zhan Shi , Ria Stevens , Vincent X. Wang

We consider a type of nonnormal approximation of infinitely divisible distributions that incorporates compound Poisson, Gamma, and normal distributions. The approximation relies on achieving higher orders of cumulant matching, to obtain…

Probability · Mathematics 2013-04-24 Zhiyi Chi

The Poisson multinomial distribution (PMD) describes the distribution of the sum of $n$ independent but non-identically distributed random vectors, in which each random vector is of length $m$ with 0/1 valued elements and only one of its…

Computation · Statistics 2022-01-13 Zhengzhi Lin , Yueyao Wang , Yili Hong

In this paper, we first consider a family of constraints given by straight lines. For a uniform probability distribution, we determine the constrained optimal sets of $n$-points and the corresponding $n$th constrained quantization errors…

Probability · Mathematics 2025-09-26 Pavjeet Singh , S. K. Katiyar , Megha Pandey , Mrinal K. Roychowdhury

Auction theory traditionally assumes that bidders' valuation distributions are known to the auctioneer, such as in the celebrated, revenue-optimal Myerson auction. However, this theory does not describe how the auctioneer comes to possess…

Computer Science and Game Theory · Computer Science 2014-07-11 Avrim Blum , Yishay Mansour , Jamie Morgenstern

We present an approximation algorithm for the Prize-collecting Ordered Traveling Salesman Problem (PCOTSP), which simultaneously generalizes the Prize-collecting TSP and the Ordered TSP. The Prize-collecting TSP is well-studied and has a…

Data Structures and Algorithms · Computer Science 2024-11-25 Morteza Alimi , Tobias Mömke , Michael Ruderer

Consider $n$ players whose "scores" are independent and identically distributed values $\{X_i\}_{i=1}^n$ from some discrete distribution $F$. We pay special attention to the cases where (i) $F$ is geometric with parameter $p\to0$ and (ii)…

Probability · Mathematics 2012-04-12 Julia Eaton , Anant Godbole , Betsy Sinclair

The generalised random graph contains $n$ vertices with positive i.i.d. weights. The probability of adding an edge between two vertices is increasing in their weights. We require the weight distribution to have finite second moments and…

Probability · Mathematics 2026-04-01 Matthias Lienau

Approximation theory is concerned with the ability to approximate functions by simpler and more easily calculated functions. The first question we ask in approximation theory concerns the {\it possibility of approximation}. Is the given…

Classical Analysis and ODEs · Mathematics 2007-05-23 Allan Pinkus

The paper introduces a modified version of the classical Coupon Collector's Problem entailing exchanges and cooperation between multiple players. Results of the development show that, within a proper Markov framework, the complexity of the…

Discrete Mathematics · Computer Science 2009-12-15 R. Rovatti , C. Passerini , G. Mazzini

Two new information-theoretic methods are introduced for establishing Poisson approximation inequalities. First, using only elementary information-theoretic techniques it is shown that, when $S_n=\sum_{i=1}^nX_i$ is the sum of the (possibly…

Probability · Mathematics 2010-10-21 Ioannis Kontoyiannis , Peter Harremoes , Oliver Johnson

Several results of large deviations are obtained for distributions that are associated with the Poisson--Dirichlet distribution and the Ewens sampling formula when the parameter $\theta$ approaches infinity. The motivation for these results…

Probability · Mathematics 2007-11-06 Shui Feng

The Pitman-Yor process is a random discrete measure. The random weights or masses follow the two-parameter Poisson-Dirichlet distribution with parameters $0<\alpha<1, \theta>-\alpha$. The parameters $\alpha$ and $\theta$ correspond to the…

Probability · Mathematics 2016-02-29 Shui Feng , Fuqing Gao , Youzhou Zhou

Polling systems are a well-established subject in queueing theory. However, their formal treatments generally rely heavily on relatively sophisticated theoretical tools, such as moment generating functions and Laplace transforms, and…

Systems and Control · Computer Science 2012-11-06 Field Cady

Consider the family of power divergence statistics based on $n$ trials, each leading to one of $r$ possible outcomes. This includes the log-likelihood ratio and Pearson's statistic as important special cases. It is known that in certain…

Probability · Mathematics 2024-11-08 Fraser Daly

The study of the number of collisions in a Poisson-Dirichlet coalescent leads to the analysis of the following version of a stochastic leader-elec\-tion algorithm. Consider an infinite family of persons, labeled by $1,2,3,\ldots$, who…

Probability · Mathematics 2016-11-15 Gerold Alsmeyer , Zakhar Kabluchko , Alexander Marynych

In a Cox model, the partial likelihood, as the product of a series of conditional probabilities, is used to estimate the regression coefficients. In practice, those conditional probabilities are approximated by risk score ratios based on a…

Methodology · Statistics 2025-02-27 Youngjin Cho , Yili Hong , Pang Du