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We consider the problem of graph searching with prediction recently introduced by Banerjee et al. (2022). In this problem, an agent, starting at some vertex $r$ has to traverse a (potentially unknown) graph $G$ to find a hidden goal node…

Data Structures and Algorithms · Computer Science 2024-03-19 Adela Frances DePavia , Erasmo Tani , Ali Vakilian

Graph classes of bounded tree rank were introduced recently in the context of the model checking problem for first-order logic of graphs. These graph classes are a common generalization of graph classes of bounded degree and bounded…

Discrete Mathematics · Computer Science 2025-10-08 Jakub Gajarský , Rose McCarty

Random graph models have played a dominant role in the theoretical study of networked systems. The Poisson random graph of Erdos and Renyi, in particular, as well as the so-called configuration model, have served as the starting point for…

Statistical Mechanics · Physics 2014-12-03 M. E. J. Newman , Travis Martin

Dense subgraph discovery is a fundamental primitive in graph and hypergraph analysis which among other applications has been used for real-time story detection on social media and improving access to data stores of social networking…

Data Structures and Algorithms · Computer Science 2024-02-23 Yufan Huang , David F. Gleich , Nate Veldt

A sequence of graphs is FO-convergent if the probability of satisfaction of every first-order formula converges. A graph modeling is a graph, whose domain is a standard probability space, with the property that every definable set is Borel.…

Combinatorics · Mathematics 2026-04-15 J. Nesetril , P. Ossona de Mendez

We introduce differential games for FO logic of graphs, a variant of Ehrenfeucht-Fra\"{i}ss\'e games in which the game is played on only one graph and the moves of both players restricted. We prove that, in a certain sense, these games are…

Logic in Computer Science · Computer Science 2020-07-23 Jakub Gajarský , Maximilian Gorsky , Stephan Kreutzer

Recent years have seen significant progress in the study of dynamic graph algorithms, and most notably, the introduction of strong lower bound techniques for them (e.g., Henzinger, Krinninger, Nanongkai and Saranurak, STOC 2015; Larsen and…

Data Structures and Algorithms · Computer Science 2025-02-19 Uri Meir , Ami Paz

Archdeacon (1987) proved that graphs embeddable on a fixed surface can be $3$-coloured so that each colour class induces a subgraph of bounded maximum degree. Edwards, Kang, Kim, Oum and Seymour (2015) proved that graphs with no…

Combinatorics · Mathematics 2019-07-15 Patrice Ossona de Mendez , Sang-il Oum , David R. Wood

The study of extremal problems for set mappings has a long history. It was introduced in 1958 by Erd\H{o}s and Hajnal, who considered the case of cliques in graphs and hypergraphs. Recently, Caro, Patk\'os, Tuza and Vizer revisited this…

Combinatorics · Mathematics 2026-01-05 Lior Gishboliner , Zhihan Jin , Benny Sudakov

Deep learning models have been shown to be vulnerable to adversarial attacks. This perception led to analyzing deep learning models not only from the perspective of their performance measures but also their robustness to certain types of…

Machine Learning · Computer Science 2021-10-13 M. Ben Amor , J. Stier , M. Granitzer

We show that for sufficiently large $d$ and for $t\geq d+1$, there is a graph $G$ with average degree $(1-\varepsilon)\lambda t \sqrt{\ln d}$ such that almost every graph $H$ with $t$ vertices and average degree $d$ is not a minor of $G$,…

Combinatorics · Mathematics 2020-12-14 Sergey Norin , Bruce Reed , Andrew Thomason , David R. Wood

In this paper, we present several density-type theorems which show how to find a copy of a sparse bipartite graph in a graph of positive density. Our results imply several new bounds for classical problems in graph Ramsey theory and improve…

Combinatorics · Mathematics 2007-11-12 Jacob Fox , Benny Sudakov

We develop an algorithmic framework for graph colouring that reduces the problem to verifying a local probabilistic property of the independent sets. With this we give, for any fixed $k\ge 3$ and $\varepsilon>0$, a randomised…

Data Structures and Algorithms · Computer Science 2020-04-16 Ewan Davies , Ross J. Kang , François Pirot , Jean-Sébastien Sereni

Finding densely connected groups of nodes in networks is a widely used tool for analysis in graph mining. A popular choice for finding such groups is to find subgraphs with a high average degree. While useful, interpreting such subgraphs…

Social and Information Networks · Computer Science 2023-09-08 Iiro Kumpulainen , Nikolaj Tatti

A dynamic graph algorithm is a data structure that answers queries about a property of the current graph while supporting graph modifications such as edge insertions and deletions. Prior work has shown strong conditional lower bounds for…

Data Structures and Algorithms · Computer Science 2023-01-30 Monika Henzinger , Ami Paz , A. R. Sricharan

We resolve a number of long-standing open problems in online graph coloring. More specifically, we develop tight lower bounds on the performance of online algorithms for fundamental graph classes. An important contribution is that our…

Data Structures and Algorithms · Computer Science 2017-07-04 Susanne Albers , Sebastian Schraink

Several algorithmic meta-theorems on kernelization have appeared in the last years, starting with the result of Bodlaender et al. [FOCS 2009] on graphs of bounded genus, then generalized by Fomin et al. [SODA 2010] to graphs excluding a…

Data Structures and Algorithms · Computer Science 2014-11-21 Valentin Garnero , Christophe Paul , Ignasi Sau , Dimitrios M. Thilikos

We obtain the scaling limits of random graphs drawn uniformly in three families of intersection graphs: permutation graphs, circle graphs, and unit interval graphs. The two first families typically generate dense graphs, in these cases we…

Probability · Mathematics 2024-02-12 Frédérique Bassino , Mathilde Bouvel , Valentin Féray , Lucas Gerin , Adeline Pierrot

Since their introduction by Kipf and Welling in $2017$, a primary use of graph convolutional networks is transductive node classification, where missing labels are inferred within a single observed graph and its feature matrix. Despite the…

Machine Learning · Statistics 2025-09-09 Nils Detering , Luca Galimberti , Anastasis Kratsios , Giulia Livieri , A. Martina Neuman

We show that every locally sparse graph contains a linearly sized expanding subgraph. For constants $c_1>c_2>1$, $0<\alpha<1$, a graph $G$ on $n$ vertices is called a $(c_1,c_2,\alpha)$-graph if it has at least $c_1n$ edges, but every…

Combinatorics · Mathematics 2017-05-04 Michael Krivelevich
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