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In this paper, we develop a general theory on the coverage probability of random intervals defined in terms of discrete random variables with continuous parameter spaces. The theory shows that the minimum coverage probabilities of random…

Statistics Theory · Mathematics 2011-04-12 Xinjia Chen

We initiate a systematic investigation of endomorphisms of graph C*-algebras C*(E), extending several known results on endomorphisms of the Cuntz algebras O_n. Most but not all of this study is focused on endomorphisms which permute the…

Operator Algebras · Mathematics 2013-01-11 Roberto Conti , Jeong Hee Hong , Wojciech Szymanski

Sampling random graphs is essential in many applications, and often algorithms use Markov chain Monte Carlo methods to sample uniformly from the space of graphs. However, often there is a need to sample graphs with some property that we are…

Social and Information Networks · Computer Science 2018-10-29 Caitlin Gray , Lewis Mitchell , Matthew Roughan

In order to model entanglements of polymers in a confined region, we consider the linking numbers and writhes of cycles in random linear embeddings of complete graphs in a cube. Our main results are that for a random linear embedding of…

Geometric Topology · Mathematics 2016-02-02 Erica Flapan , Kenji Kozai

Let $A$ be a permutation invariant random matrix and $B$ another random matrix. We give a quantitative bound on the difference between the diagonal of the resolvent of $A+B$ and the diagonal of the resolvent of the free sum with…

Probability · Mathematics 2026-03-03 Alexis Imbert

Let $w:[0,1]^2\rightarrow [0,1]$ be a symmetric function, and consider the random process $G(n,w)$, where vertices are chosen from $[0,1]$ uniformly at random, and $w$ governs the edge formation probability. Such a random graph is said to…

Combinatorics · Mathematics 2016-09-15 Huda Chuangpishit , Mahya Ghandehari , Jeannette Janssen

A graph $G=(V,E)$ is called $d$-rigid if, for a generic embedding of its vertices in $\mathbb{R}^d$, every edge-length preserving continuous motion of the vertices preserves the distances between all pairs of non-adjacent vertices as well.…

Combinatorics · Mathematics 2026-03-02 Michael Krivelevich , Alan Lew , Peleg Michaeli

A weakly admissible mesh (WAM) on a continuum real-valued domain is a sequence of discrete grids such that the discrete maximum norm of polynomials on the grid is comparable to the supremum norm of polynomials on the domain. The asymptotic…

Numerical Analysis · Mathematics 2021-09-20 Yiming Xu , Akil Narayan

This paper investigates the problem of dynamical sampling for graph signals influenced by a constant source term. We consider signals evolving over time according to a linear dynamical system on a graph, where both the initial state and the…

Numerical Analysis · Mathematics 2025-09-23 Le Gong , Longxiu Huang

Consider a random graph process where vertices are chosen from the interval $[0,1]$, and edges are chosen independently at random, but so that, for a given vertex $x$, the probability that there is an edge to a vertex $y$ decreases as the…

Symbolic data analysis has been proposed as a technique for summarising large and complex datasets into a much smaller and tractable number of distributions -- such as random rectangles or histograms -- each describing a portion of the…

Computation · Statistics 2020-03-23 Thomas Whitaker , Boris Beranger , Scott A. Sisson

The class of complex random vectors whose covariance matrix is linearly parameterized by a basis of Hermitian Toeplitz (HT) matrices is considered, and the maximum compression ratios that preserve all second-order information are derived…

Statistics Theory · Mathematics 2016-11-15 Daniel Romero , Roberto Lopez-Valcarce , Geert Leus

This paper puts forward a new generalized polynomial dimensional decomposition (PDD), referred to as GPDD, comprising hierarchically ordered measure-consistent multivariate orthogonal polynomials in dependent random variables. Unlike the…

Numerical Analysis · Mathematics 2018-10-30 Sharif Rahman

Compression of integer sets and sequences has been extensively studied for settings where elements follow a uniform probability distribution. In addition, methods exist that exploit clustering of elements in order to achieve higher…

Information Theory · Computer Science 2014-02-11 N. Jesper Larsson

We study the k-wise independent relaxation of the usual model G(N,p) of random graphs where, as in this model, N labeled vertices are fixed and each edge is drawn with probability p, however, it is only required that the distribution of any…

Combinatorics · Mathematics 2008-04-09 Noga Alon , Asaf Nussboim

We prove a robust contraction decomposition theorem for $H$-minor-free graphs, which states that given an $H$-minor-free graph $G$ and an integer $p$, one can partition in polynomial time the vertices of $G$ into $p$ sets $Z_1,\dots,Z_p$…

Data Structures and Algorithms · Computer Science 2024-12-06 Sayan Bandyapadhyay , William Lochet , Daniel Lokshtanov , Dániel Marx , Pranabendu Misra , Daniel Neuen , Saket Saurabh , Prafullkumar Tale , Jie Xue

In the first part of this paper, we consider weighted domination in the case where the vertices of the complete graph on~\(n\) vertices are equipped with independent and identically distributed (i.i.d.) weights. We use the probabilistic…

Probability · Mathematics 2023-01-16 Ghurumuruhan Ganesan

A random graph order is a partial order obtained from a random graph on $[n]$ by taking the transitive closure of the adjacency relation. The dimension of the random graph orders from random bipartite graphs $B(n,n,p)$ and from $G(n,p)$…

Combinatorics · Mathematics 2026-01-27 Pu Gao , Arnav Kumar

We prove large (and moderate) deviations for a class of linear combinations of spacings generated by i.i.d. exponentially distributed random variables. We allow a wide class of coefficients which can be expressed in terms of continuous…

Probability · Mathematics 2021-09-07 Camilla Calì , Maria Longobardi , Claudio Macci , Barbara Pacchiarotti

Letting $\mathcal{M}$ denote the space of finite measures on $\mathbb{N}$, and $\mu_\lambda\in\mathcal{M}$ denote the Poisson distribution with parameter $\lambda$, the function $W:[0,1]^2\to\mathcal{M}$ given by \[ W(x,y)=\mu_{c\log x\log…

Combinatorics · Mathematics 2017-01-25 Ágnes Backhausz , Dávid Kunszenti-Kovács