English
Related papers

Related papers: Record-biased permutations and their permuton limi…

200 papers

For a distribution $p:=\{p_k\}_{k=1}^\infty$ on the positive integers, there are two natural ways to construct a random permutation in $S_n$ or of $\mathbb{N}$ from IID samples from $p$--the $p$-biased construction and the $p$-shifted…

Probability · Mathematics 2021-02-23 Ross G. Pinsky

This article presents a modern deterministic framework for the study of leading significant digit distributions in numerical data. Rather than relying on traditional probabilistic or mixture-based explanations, we demonstrate that the…

Machine Learning · Statistics 2025-08-20 Vladimir Berman

We consider uniform random permutations of length $n$ conditioned to have no cycle longer than $n^\beta$ with $0<\beta<1$, in the limit of large $n$. Since in unconstrained uniform random permutations most of the indices are in cycles of…

Probability · Mathematics 2018-12-21 Volker Betz , Helge Schäfer , Dirk Zeindler

We consider the question of computing the distribution of a permutation statistics over restricted permutations via enumeration schemes. The restricted permutations are those avoiding sets of vincular patterns (which include both classical…

Combinatorics · Mathematics 2014-01-03 Andrew M. Baxter

Learning generative models for graph-structured data is challenging because graphs are discrete, combinatorial, and the underlying data distribution is invariant to the ordering of nodes. However, most of the existing generative models for…

Machine Learning · Computer Science 2020-03-03 Chenhao Niu , Yang Song , Jiaming Song , Shengjia Zhao , Aditya Grover , Stefano Ermon

In this paper we study a class of dynamical systems generated by iterations of multivariate permutation polynomial systems which lead to polynomial growth of the degrees of these iterations. Using these estimates and the same techniques…

Number Theory · Mathematics 2010-01-10 Alina Ostafe

Learning distributions over permutations is a fundamental problem in machine learning, with applications in ranking, combinatorial optimization, structured prediction, and data association. Existing methods rely on mixtures of parametric…

Machine Learning · Computer Science 2025-06-02 Daniel Severo , Brian Karrer , Niklas Nolte

We prove some general results about the asymptotics of the distribution of the number of cycles of given length of a random permutation whose distribution is invariant under conjugation. These results were first established to be applied in…

Probability · Mathematics 2009-01-16 Florent Benaych-Georges

We describe the limit (for two topologies) of large uniform random square permutations, i.e., permutations where every point is a record. The starting point for all our results is a sampling procedure for asymptotically uniform square…

Probability · Mathematics 2020-11-10 Jacopo Borga , Erik Slivken

Permutation entropy measures the complexity of deterministic time series via a data symbolic quantization consisting of rank vectors called ordinal patterns or just permutations. The reasons for the increasing popularity of this entropy in…

Data Analysis, Statistics and Probability · Physics 2021-03-08 José M. Amigó , Roberto Dale , Piergiulio Tempesta

The assumption that response and predictor belong to the same statistical unit may be violated in practice. Unbiased estimation and recovery of true label ordering based on unlabeled data are challenging tasks and have attracted increasing…

Methodology · Statistics 2022-06-24 Guanhua Fang , Ping Li

We consider random permutation matrices following a one-parameter family of deformations of the uniform distribution, called Ewens' measures, and modifications of these matrices where the entries equal to one are replaced by i.i.d uniform…

Probability · Mathematics 2018-03-12 Valentin Bahier

We derive a large deviation principle for random permutations induced by probability measures of the unit square, called permutons. These permutations are called $\mu$-random permutations. We also introduce and study a new general class of…

Probability · Mathematics 2023-04-04 Jacopo Borga , Sayan Das , Sumit Mukherjee , Peter Winkler

Recently, diffusion probabilistic models (DPMs) have achieved promising results in diverse generative tasks. A typical DPM framework includes a forward process that gradually diffuses the data distribution and a reverse process that…

Machine Learning · Computer Science 2023-10-31 Tianyu Pang , Cheng Lu , Chao Du , Min Lin , Shuicheng Yan , Zhijie Deng

The purpose of this article is to present a general method to find limiting laws for some renormalized statistics on random permutations. The model considered here is Ewens sampling model, which generalizes uniform random permutations. We…

Probability · Mathematics 2013-10-28 Valentin Féray

We prove several general formulas for the distributions of various permutation statistics over any set of permutations whose quasisymmetric generating function is a symmetric function. Our formulas involve certain kinds of plethystic…

Combinatorics · Mathematics 2020-08-21 Ira M. Gessel , Yan Zhuang

We initiate the study of limit shapes for random permutations avoiding a given pattern. Specifically, for patterns of length 3, we obtain delicate results on the asymptotics of distributions of positions of numbers in the permutations. We…

Combinatorics · Mathematics 2013-12-02 Sam Miner , Igor Pak

In this paper we introduce randomized pivots for the means of short and long memory linear processes. We show that, under the same conditions, these pivots converge in distribution to the same limit as that of their classical non-randomized…

Statistics Theory · Mathematics 2014-05-14 Miklos Csorgo , Masoud M Nasari , Mohamedou Ould-Haye

The objects of our interest are the so-called $A$-permutations, which are permutations whose cycle length lie in a fixed set $A$. They have been extensively studied with respect to the uniform or the Ewens measure. In this paper, we extend…

Probability · Mathematics 2013-02-26 Ashkan Nikeghbali , Julia Storm , Dirk Zeindler

In this paper, we introduce a convergence notion for ordered selections. Our convergence notion is based on subpermutation densities and convergences of the marginal distributions. A particular case of this convergence is the well-known…

Probability · Mathematics 2025-11-18 B. Fazekas , I. Fazekas