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When sampling multiple signals, the correlation between the signals can be exploited to reduce the overall number of samples. In this paper, we study the sampling theory of multiple correlated signals, using correlation to sample them at…

Signal Processing · Electrical Eng. & Systems 2022-10-11 Zhongyi Ni , Feng Ji , Hang Sheng , Hui Feng , Bo Hu

In many scientific tasks we are interested in discovering whether there exist any correlations in our data. This raises many questions, such as how to reliably and interpretably measure correlation between a multivariate set of attributes,…

Machine Learning · Computer Science 2019-09-02 Panagiotis Mandros , Mario Boley , Jilles Vreeken

Inhomogeneous random graph models encompass many network models such as stochastic block models and latent position models. We consider the problem of statistical estimation of the matrix of connection probabilities based on the…

Statistics Theory · Mathematics 2017-09-14 Olga Klopp , Alexandre B. Tsybakov , Nicolas Verzelen

In this paper, we present an algorithm for computing a feedback vertex set of a unit disk graph of size $k$, if it exists, which runs in time $2^{O(\sqrt{k})}(n+m)$, where $n$ and $m$ denote the numbers of vertices and edges, respectively.…

Computational Geometry · Computer Science 2021-07-09 Shinwoo An , Eunjin Oh

We study asymptotic behaviour of the correlation functions of bipartite sparse random $N\times N$ matrices. We assume that the graphs have $N$ vertices, the ratio of parts is $\displaystyle\frac{\alpha}{1-\alpha}$ and the average number of…

Mathematical Physics · Physics 2025-08-12 Valentin Vengerovsky

In this paper, we consider the weighted graph matching problem with partially disclosed correspondences between a number of anchor nodes. Our construction exploits recently introduced node signatures based on graph Laplacians, namely the…

Computer Vision and Pattern Recognition · Computer Science 2018-04-12 Nan Hu , Raif M. Rustamov , Leonidas Guibas

This paper investigates the limiting behaviour of degree-degree correlation metrics for sequences of random graphs under a general assumption of local convergence in probability. We establish convergence results for Pearson's correlation…

Probability · Mathematics 2026-02-20 Andrei-Eugeniu Patularu , Pim van der Hoorn

Measuring the topological overlap of two graphs becomes important when assessing the changes between temporally adjacent graphs in a time-evolving network. Current methods depend on the fraction of nodes that have persisting edges. This…

Physics and Society · Physics 2014-03-06 Fiona Pigott , Mauricio Rene Herrera Marin

We analyse graphs in which each vertex is assigned random coordinates in a geometric space of arbitrary dimensionality and only edges between adjacent points are present. The critical connectivity is found numerically by examining the size…

Statistical Mechanics · Physics 2009-11-07 Jesper Dall , Michael Christensen

In recent years there has been increased interest in extremal problems for "counting" parameters of graphs. For example, the Kahn-Zhao theorem gives an upper bound on the number of independent sets in a $d$-regular graph. In the same…

Combinatorics · Mathematics 2013-10-08 L. Keough , A. J. Radcliffe

We propose graph kernels based on subgraph matchings, i.e. structure-preserving bijections between subgraphs. While recently proposed kernels based on common subgraphs (Wale et al., 2008; Shervashidze et al., 2009) in general can not be…

Machine Learning · Computer Science 2012-07-03 Nils Kriege , Petra Mutzel

We study the properties of the giant connected component in random graphs with arbitrary degree distribution. We concentrate on the degree-degree correlations. We show that the adjoining nodes in the giant connected component are correlated…

Statistical Mechanics · Physics 2010-05-11 Piotr Bialas , Andrzej K. Oleś

(a) We propose a ``static'' construction procedure for random networks with given correlations of the degrees of the nearest-neighbor vertices. This is an equilibrium graph, maximally random under the constraint that its degree-degree…

Statistical Mechanics · Physics 2007-05-23 S. N. Dorogovtsev , J. F. F. Mendes , A. N. Samukhin

Finding $k$-cores in graphs is a valuable and effective strategy for extracting dense regions of otherwise sparse graphs. We focus on the important problem of maintaining cores on rapidly changing dynamic graphs, where batches of edge…

Data Structures and Algorithms · Computer Science 2022-03-25 Kasimir Gabert , Ali Pınar , Ümit V. Çatalyürek

In this paper, we focus on the study of immanantal polynomials for linear combination matrices composed of the degree matrix and adjacency matrix of a graph. First, applying the concept of vertex orientation for general graphs, we provide a…

Combinatorics · Mathematics 2026-04-07 Xiangshuai Dong , Tingzeng Wu

Random $s$-intersection graphs have recently received much interest in a wide range of application areas. Broadly speaking, a random $s$-intersection graph is constructed by first assigning each vertex a set of items in some random manner,…

Combinatorics · Mathematics 2014-11-19 Jun Zhao , Osman Yağan , Virgil Gligor

We study random graphs with arbitrary distributions of expected degree and derive expressions for the spectra of their adjacency and modularity matrices. We give a complete prescription for calculating the spectra that is exact in the limit…

Social and Information Networks · Computer Science 2013-02-04 Raj Rao Nadakuditi , M. E. J. Newman

Motivated from the theory of quantum error correcting codes, we investigate a combinatorial problem that involves a symmetric $n$-vertices colourable graph and a group of operations (colouring rules) on the graph: find the minimum sequence…

Combinatorics · Mathematics 2014-09-10 German Luna , Samuel Reid , Bianca De Sanctis , Vlad Gheorghiu

A common approach for designing scalable algorithms for massive data sets is to distribute the computation across, say $k$, machines and process the data using limited communication between them. A particularly appealing framework here is…

Data Structures and Algorithms · Computer Science 2017-05-24 Sepehr Assadi , Sanjeev Khanna

A random coefficient autoregressive process is deeply investigated in which the coefficients are correlated. First we look at the existence of a strictly stationary causal solution, we give the second-order stationarity conditions and the…

Statistics Theory · Mathematics 2018-03-29 Frédéric Proïa , Marius Soltane
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