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We consider a generalized version of the (weighted) one-center problem on graphs. Given an undirected graph $G$ of $n$ vertices and $m$ edges and a positive integer $k\leq n$, the problem aims to find a point in $G$ so that the maximum…

Data Structures and Algorithms · Computer Science 2025-01-22 Jingru Zhang

An identifying code of a graph is a subset of its vertices such that every vertex of the graph is uniquely identified by the set of its neighbours within the code. We show a dichotomy for the size of the smallest identifying code in classes…

Discrete Mathematics · Computer Science 2017-04-17 Nicolas Bousquet , Aurélie Lagoutte , Zhentao Li , Aline Parreau , Stéphan Thomassé

Using dominating sets to separate vertices of graphs is a well-studied problem in the larger domain of identification problems. In such problems, the objective is to choose a suitable dominating set $C$ of a graph $G$ which is also…

Combinatorics · Mathematics 2025-10-13 Dipayan Chakraborty , Annegret K. Wagler

In 2020, we initiated a systematic study of graph classes in which the treewidth can only be large due to the presence of a large clique, which we call $(\mathrm{tw},\omega)$-bounded. While $(\mathrm{tw},\omega)$-bounded graph classes are…

Combinatorics · Mathematics 2023-10-18 Clément Dallard , Martin Milanič , Kenny Štorgel

We show how to find and efficiently maintain maximal k-edge-connected subgraphs in undirected graphs. In particular, we provide the following results. (1) A general framework for maintaining the maximal k-edge-connected subgraphs upon…

Data Structures and Algorithms · Computer Science 2023-05-02 Loukas Georgiadis , Giuseppe F. Italiano , Evangelos Kosinas , Debasish Pattanayak

Contrastive learning methods have attracted considerable attention due to their remarkable success in analyzing graph-structured data. Inspired by the success of contrastive learning, we propose a novel framework for contrastive…

Machine Learning · Computer Science 2023-06-21 Xiaojuan Zhang , Jun Fu , Shuang Li

We study edge-decompositions of highly connected graphs into copies of a given tree. In particular we attack the following conjecture by Bar\'at and Thomassen: for each tree $T$, there exists a natural number $k_T$ such that if $G$ is a…

Combinatorics · Mathematics 2012-03-09 János Barát , Dániel Gerbner

Graph labeling problems have been widely studied in the last decades and have a vast area of application. In this work, we study the recently introduced S-labeling problem, in which the nodes get labeled using labels from 1 to |V | and for…

Optimization and Control · Mathematics 2019-09-12 Markus Sinnl

A graph is called a sum graph if its vertices can be labelled by distinct positive integers such that there is an edge between two vertices if and only if the sum of their labels is the label of another vertex of the graph. Most papers on…

Data Structures and Algorithms · Computer Science 2022-01-06 Henning Fernau , Kshitij Gajjar

We investigate the problem of sequentially predicting the binary labels on the nodes of an arbitrary weighted graph. We show that, under a suitable parametrization of the problem, the optimal number of prediction mistakes can be…

Machine Learning · Computer Science 2012-12-27 Nicolo' Cesa-Bianchi , Claudio Gentile , Fabio Vitale , Giovanni Zappella

Text generation from AMR requires mapping a semantic graph to a string that it annotates. Transformer-based graph encoders, however, poorly capture vertex dependencies that may benefit sequence prediction. To impose order on an encoder, we…

Computation and Language · Computer Science 2021-09-03 Lisa Jin , Daniel Gildea

The local tree-width of a graph G=(V,E) is the function ltw^G: N -> N that associates with every natural number r the maximal tree-width of an r-neighborhood in G. Our main graph theoretic result is a decomposition theorem for graphs with…

Combinatorics · Mathematics 2007-05-23 Martin Grohe

From social science to biology, numerous applications often rely on graphlets for intuitive and meaningful characterization of networks at both the global macro-level as well as the local micro-level. While graphlets have witnessed a…

Social and Information Networks · Computer Science 2016-02-17 Nesreen K. Ahmed , Jennifer Neville , Ryan A. Rossi , Nick Duffield , Theodore L. Willke

We consider the problem of designing a succinct data structure for {\it path graphs} (which are a proper subclass of chordal graphs and a proper superclass of interval graphs) on $n$ vertices while supporting degree, adjacency, and…

Data Structures and Algorithms · Computer Science 2023-03-03 Girish Balakrishnan , Sankardeep Chakraborty , N S Narayanaswamy , Kunihiko Sadakane

Massive networks have shown that the determination of dense subgraphs, where vertices interact a lot, is necessary in order to visualize groups of common interest, and therefore be able to decompose a big graph into smaller structures. Many…

Social and Information Networks · Computer Science 2016-04-29 Etienne Callies , Tomás Yany-Anich

In this paper we study spread codes: a family of constant-dimension codes for random linear network coding. In other words, the codewords are full-rank matrices of size (k x n) with entries in a finite field F_q. Spread codes are a family…

Information Theory · Computer Science 2012-06-08 Elisa Gorla , Felice Manganiello , Joachim Rosenthal

We here investigate on the complexity of computing the \emph{tree-length} and the \emph{tree-breadth} of any graph $G$, that are respectively the best possible upper-bounds on the diameter and the radius of the bags in a tree decomposition…

Computational Complexity · Computer Science 2016-01-11 Guillaume Ducoffe , Sylvain Legay , Nicolas Nisse

A subgraph of an edge-coloured graph is called rainbow if all its edges have distinct colours. The study of rainbow subgraphs goes back more than two hundred years to the work of Euler on Latin squares. Since then rainbow structures have…

Combinatorics · Mathematics 2018-12-11 Richard Montgomery , Alexey Pokrovskiy , Benny Sudakov

The (variational) graph auto-encoder and its variants have been popularly used for representation learning on graph-structured data. While the encoder is often a powerful graph convolutional network, the decoder reconstructs the graph…

Machine Learning · Computer Science 2019-11-27 Han Shi , Haozheng Fan , James T. Kwok

The paper presents fault-tolerant (FT) labeling schemes for general graphs, as well as, improved FT routing schemes. For a given $n$-vertex graph $G$ and a bound $f$ on the number of faults, an $f$-FT connectivity labeling scheme is a…

Data Structures and Algorithms · Computer Science 2021-06-02 Michal Dory , Merav Parter