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We present a constraint model for the problem of producing a tree decomposition of a graph. The inputs to the model are a simple graph G, the number of nodes in the desired tree decomposition and the maximum cardinality of each node in that…

Discrete Mathematics · Computer Science 2019-08-08 Benjamin Bumpus , Patrick Prosser , James Trimble

We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to solve a maximum likelihood problem with an added l_1-norm…

Artificial Intelligence · Computer Science 2007-07-06 Onureena Banerjee , Laurent El Ghaoui , Alexandre d'Aspremont

The degree-diameter problem seeks to find the maximum possible order of a graph with a given (maximum) degree and diameter. It is known that graphs attaining the maximum possible value (the Moore bound) are extremely rare, but much activity…

Combinatorics · Mathematics 2016-05-03 Dominique Buset , Mourad El Amiri , Grahame Erskine , Hebert Pérez-Rosés , Mirka Miller

In this article we introduce a simple tool to derive polynomial upper bounds for the probability of observing unusually large maximal components in some models of random graphs when considered at criticality. Specifically, we apply our…

Probability · Mathematics 2022-02-01 Umberto De Ambroggio

Upper and lower bounds on the error probability of linear codes under maximum-likelihood (ML) decoding are shortly surveyed and applied to ensembles of codes on graphs. For upper bounds, focus is put on Gallager bounding techniques and…

Information Theory · Computer Science 2007-07-13 Igal Sason , Shlomo Shamai

Applications on inference of biological networks have raised a strong interest in the problem of graph estimation in high-dimensional Gaussian graphical models. To handle this problem, we propose a two-stage procedure which first builds a…

Statistics Theory · Mathematics 2012-02-17 Christophe Giraud , Sylvie Huet , Nicolas Verzelen

We prove almost sure convergence of the maximum degree in an evolving graph model combining a growing number of local choices with sublinear preferential attachment. At each step in the growth of the graph, a new vertex is introduced. Then…

Probability · Mathematics 2019-11-19 Yury Malyshkin

We study a number of graph exploration problems in the following natural scenario: an algorithm starts exploring an undirected graph from some seed node; the algorithm, for an arbitrary node $v$ that it is aware of, can ask an oracle to…

Data Structures and Algorithms · Computer Science 2017-10-25 Flavio Chierichetti , Shahrzad Haddadan

Let $G = (V,E)$ be a graph, and for each $e \in E(G)$, let $L_e$ be a list of real numbers. Let $w:E(G) \to \cup_{e \in E(G)}L_e$ be an edge weighting function such that $w(e) \in L_e$ for each $e \in E(G)$, and let $c_w$ be the vertex…

Combinatorics · Mathematics 2014-01-28 Ben Seamone

How to obtain a graph from data samples is an important problem in graph signal processing. One way to formulate this graph learning problem is based on Gaussian maximum likelihood estimation, possibly under particular topology constraints.…

Signal Processing · Electrical Eng. & Systems 2017-11-02 Keng-Shih Lu , Antonio Ortega

We consider the problem of estimating the topology of multiple networks from nodal observations, where these networks are assumed to be drawn from the same (unknown) random graph model. We adopt a graphon as our random graph model, which is…

Machine Learning · Statistics 2022-02-14 Madeline Navarro , Santiago Segarra

There are many methods to find a maximum (or maximal) clique in large networks. Due to the nature of combinatorics, computation becomes exponentially expensive as the number of vertices in a graph increases. Thus, there is a need for…

Social and Information Networks · Computer Science 2022-07-27 S. Y. Chan , K. Morgan , J. Ugon

High-dimensional feature selection is a central problem in a variety of application domains such as machine learning, image analysis, and genomics. In this paper, we propose graph-based tests as a useful basis for feature selection. We…

Methodology · Statistics 2024-08-13 Swarnadip Ghosh , Somabha Mukherjee , Divyansh Agarwal , Yichen He , Mingzhi Song , Xuejiao Pei

We consider discrete graphical models Markov with respect to a graph $G$ and propose two distributed marginal methods to estimate the maximum likelihood estimate of the canonical parameter of the model. Both methods are based on a…

Machine Learning · Statistics 2013-10-22 Helene Massam , Nanwei Wang

The present work deals with active sampling of graph nodes representing training data for binary classification. The graph may be given or constructed using similarity measures among nodal features. Leveraging the graph for classification…

Machine Learning · Statistics 2018-10-17 Dimitris Berberidis , Georgios B. Giannakis

Let $\text{ch}(G)$ denote the choice number of a graph $G$ (also called "list chromatic number" or "choosability" of $G$). Noel, Reed, and Wu proved the conjecture of Ohba that $\text{ch}(G)=\chi(G)$ when $|V(G)|\le 2\chi(G)+1$. We extend…

Combinatorics · Mathematics 2014-08-28 Jonathan A. Noel , Douglas B. West , Hehui Wu , Xuding Zhu

Limiting distributions are derived for the sparse connected components that are present when a random graph on $n$ vertices has approximately $\half n$ edges. In particular, we show that such a graph consists entirely of trees, unicyclic…

Probability · Mathematics 2008-02-03 Svante Janson , Donald E. Knuth , Tomasz Łuczak , Boris Pittel

We consider the random graph $G_{n, {\bf d}}$ chosen uniformly at random from the set of all graphs with a given sparse degree sequence ${\bf d}$. We assume ${\bf d}$ has minimum degree at least 4, at most a power law tail, and place one…

Combinatorics · Mathematics 2020-01-16 Tony Johansson

We develop an improved bound for the chromatic number of graphs of maximum degree $\Delta$ under the assumption that the number of edges spanning any neighbourhood is at most $(1-\sigma)\binom{\Delta}{2}$ for some fixed $0<\sigma<1$. The…

Combinatorics · Mathematics 2022-09-13 Eoin Hurley , Rémi de Joannis de Verclos , Ross J. Kang

In this paper, we derive the limit of experiments for one parameter Ising models on dense regular graphs. In particular, we show that the limiting experiment is Gaussian in the low temperature regime, non Gaussian in the critical regime,…

Statistics Theory · Mathematics 2023-05-11 Yuanzhe Xu , Sumit Mukherjee