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Related papers: Smoothed analysis for graph isomorphism

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An explicit algorithm is presented for testing whether two non-directed graphs are isomorphic or not. It is shown that for a graph of n vertices, the number of n independent operations needed for the test is polynomial in n. A proof that…

Data Structures and Algorithms · Computer Science 2007-05-23 Moshe Schwartz

This paper studies the problem of detecting anomalous graphs using a machine learning model trained on only normal graphs, which has many applications in molecule, biology, and social network data analysis. We present a self-discriminative…

Machine Learning · Computer Science 2023-10-11 Jinyu Cai , Yunhe Zhang , Jicong Fan

The Weisfeiler-Leman (WL) algorithm is a well-known combinatorial procedure for detecting symmetries in graphs and it is widely used in graph-isomorphism tests. It proceeds by iteratively refining a colouring of vertex tuples. The number of…

Discrete Mathematics · Computer Science 2021-07-01 Martin Grohe , Sandra Kiefer

The Weisfeiler-Leman (WL) algorithms form a family of incomplete approaches to the graph isomorphism problem. They recently found various applications in algorithmic group theory and machine learning. In fact, the algorithms form a…

Discrete Mathematics · Computer Science 2025-10-29 Thomas Schneider , Pascal Schweitzer

We present a novel neural architecture to solve graph optimization problems where the solution consists of arbitrary node labels, allowing us to solve hard problems like graph coloring. We train our model using reinforcement learning,…

Machine Learning · Computer Science 2022-05-11 Lukas Gianinazzi , Maximilian Fries , Nikoli Dryden , Tal Ben-Nun , Maciej Besta , Torsten Hoefler

In the study of deterministic distributed algorithms it is commonly assumed that each node has a unique $O(\log n)$-bit identifier. We prove that for a general class of graph problems, local algorithms (constant-time distributed algorithms)…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-12-24 Mika Göös , Juho Hirvonen , Jukka Suomela

Approximate random $k$-colouring of a graph $G$ is a well studied problem in computer science and statistical physics. It amounts to constructing a $k$-colouring of $G$ which is distributed close to {\em Gibbs distribution} in polynomial…

Discrete Mathematics · Computer Science 2016-09-21 Charilaos Efthymiou

In this paper, we consider the following graph partitioning problem: The input is an undirected graph $G=(V,E),$ a balance parameter $b \in (0,1/2]$ and a target conductance value $\gamma \in (0,1).$ The output is a cut which, if non-empty,…

Data Structures and Algorithms · Computer Science 2010-10-21 Lorenzo Orecchia , Nisheeth K. Vishnoi

Graphs with a simple spectrum admit cubic-time isomorphism testing, yet we prove that for every natural number $k$, the $k$-Weisfeiler-Leman ($k$-WL) test cannot distinguish all non-isomorphic graphs with a simple spectrum. As the WL…

Machine Learning · Computer Science 2026-05-25 Snir Hordan , Nadav Dym , Tim Seppelt

Representing patterns as labeled graphs is becoming increasingly common in the broad field of computational intelligence. Accordingly, a wide repertoire of pattern recognition tools, such as classifiers and knowledge discovery procedures,…

Computer Vision and Pattern Recognition · Computer Science 2017-05-11 Lorenzo Livi

Edge-weighted graphs play an important role in the theory of Robinsonian matrices and similarity theory, particularly via the concept of level graphs, that is, graphs obtained from an edge-weighted graph by removing all sufficiently light…

The $k$-dimensional Weisfeiler-Leman algorithm is a powerful tool in graph isomorphism testing. For an input graph $G$, the algorithm determines a canonical coloring of $s$-tuples of vertices of $G$ for each $s$ between 1 and $k$. We say…

Computational Complexity · Computer Science 2020-05-20 Frank Fuhlbrück , Johannes Köbler , Oleg Verbitsky

Recent work shows that the expressive power of Graph Neural Networks (GNNs) in distinguishing non-isomorphic graphs is exactly the same as that of the Weisfeiler-Lehman (WL) graph test. In particular, they show that the WL test can be…

We consider two independent Erd\H{o}s-R\'enyi random graphs, with possibly different parameters, and study two isomorphism problems, a graph embedding problem and a common subgraph problem. Under certain conditions on the graph parameters…

Combinatorics · Mathematics 2025-06-25 Dimitris Diamantidis , Takis Konstantopoulos , Linglong Yuan

In this paper, we propose algorithms for the graph isomorphism (GI) problem that are based on the eigendecompositions of the adjacency matrices. The eigenvalues of isomorphic graphs are identical. However, two graphs $ G_A $ and $ G_B $ can…

Discrete Mathematics · Computer Science 2019-08-14 Stefan Klus , Tuhin Sahai

Given a pair of graphs $\textbf{A}$ and $\textbf{B}$, the problems of deciding whether there exists either a homomorphism or an isomorphism from $\textbf{A}$ to $\textbf{B}$ have received a lot of attention. While graph homomorphism is…

Data Structures and Algorithms · Computer Science 2021-07-08 Silvia Butti , Victor Dalmau

An edge-weighted graph $G=(V,E)$ is called stable if the value of a maximum-weight matching equals the value of a maximum-weight fractional matching. Stable graphs play an important role in some interesting game theory problems, such as…

Data Structures and Algorithms · Computer Science 2017-11-28 Zhuan Khye Koh , Laura Sanità

In this paper we show lower bounds for a certain large class of algorithms solving the Graph Isomorphism problem, even on expander graph instances. Spielman [25] shows an algorithm for isomorphism of strongly regular expander graphs that…

Computational Complexity · Computer Science 2016-10-31 Aaron Snook , Grant Schoenebeck , Paolo Codenotti

In this paper, matching pairs of stocahstically generated graphs in the presence of generalized seed side-information is considered. The graph matching problem emerges naturally in various applications such as social network…

Information Theory · Computer Science 2021-02-15 Mahshad Shariatnasab , Farhad Shirani , Siddharth Garg , Elza Erkip

Label smoothing is a widely studied regularization technique in machine learning. However, its potential for node classification in graph-structured data, spanning homophilic to heterophilic graphs, remains largely unexplored. We introduce…

Machine Learning · Computer Science 2026-02-02 Jaeseung Heo , Moonjeong Park , Dongwoo Kim
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