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Fraud detection problems are usually formulated as a machine learning problem on a graph. Recently, Graph Neural Networks (GNNs) have shown solid performance on fraud detection. The successes of most previous methods heavily rely on rich…

Machine Learning · Computer Science 2021-10-05 Chen Wang , Yingtong Dou , Min Chen , Jia Chen , Zhiwei Liu , Philip S. Yu

Subgraphs reveal information about the geometry and functionalities of complex networks. For scale-free networks with unbounded degree fluctuations, we obtain the asymptotics of the number of times a small connected graph occurs as a…

Probability · Mathematics 2020-06-09 Remco van der Hofstad , Johan S. H. van Leeuwaarden , Clara Stegehuis

We study the problem of detecting the edge correlation between two random graphs with $n$ unlabeled nodes. This is formalized as a hypothesis testing problem, where under the null hypothesis, the two graphs are independently generated;…

Statistics Theory · Mathematics 2021-02-09 Yihong Wu , Jiaming Xu , Sophie H. Yu

We propose a simple and efficient local algorithm for graph isomorphism which succeeds for a large class of sparse graphs. This algorithm produces a low-depth canonical labeling, which is a labeling of the vertices of the graph that…

Probability · Mathematics 2023-09-20 Julia Gaudio , Miklós Z. Rácz , Anirudh Sridhar

Semi-supervised learning (SSL) is effectively used for numerous classification problems, thanks to its ability to make use of abundant unlabeled data. The main assumption of various SSL algorithms is that the nearby points on the data…

Machine Learning · Computer Science 2019-09-30 Xuan Wu , Lingxiao Zhao , Leman Akoglu

Subgraph isomorphism, also known as subgraph matching, is typically regarded as an NP-complete problem. This complexity is further compounded in practical applications where edge weights are real-valued and may be affected by measurement…

Machine Learning · Statistics 2025-06-24 Arpan Kusari , Wenbo Sun

Graph connectivity is a fundamental combinatorial optimization problem that arises in many practical applications, where usually a spanning subgraph of a network is used for its operation. However, in the real world, links may fail…

Data Structures and Algorithms · Computer Science 2022-09-13 Dimitris Fotakis , Evangelia Gergatsouli , Charilaos Pipis , Miltiadis Stouras , Christos Tzamos

Graph neural networks (GNNs) have been widely investigated in the field of semi-supervised graph machine learning. Most methods fail to exploit adequate graph information when labeled data is limited, leading to the problem of…

Machine Learning · Computer Science 2023-03-15 Linxuan Song , Wenxuan Tu , Sihang Zhou , Xinwang Liu , En Zhu

Given a function f as an oracle, the collision problem is to find two distinct inputs i and j such that f(i)=f(j), under the promise that such inputs exist. Since the security of many fundamental cryptographic primitives depends on the…

Quantum Physics · Physics 2011-11-04 Yaoyun Shi

The Graph Isomorphism problem has both theoretical and practical interest. In this paper we present an algorithm, called conauto-1.2, that efficiently tests whether two graphs are isomorphic, and finds an isomorphism if they are. This…

Data Structures and Algorithms · Computer Science 2011-06-23 Jose Luis Lopez-Presa , Antonio Fernandez Anta

We consider the problem of finding an edge in a hidden undirected graph $G = (V, E)$ with $n$ vertices, in a model where we only allowed queries that ask whether or not a subset of vertices contains an edge. We study the non-adaptive model…

Data Structures and Algorithms · Computer Science 2022-07-07 Ron Kupfer , Noam Nisan

For any particular class of graphs, algorithms for computational problems restricted to the class often rely on structural properties that depend on the specific problem at hand. This begs the question if a large set of such results can be…

Rationale discovery is defined as finding a subset of the input data that maximally supports the prediction of downstream tasks. In the context of graph machine learning, graph rationale is defined to locate the critical subgraph in the…

Machine Learning · Computer Science 2025-01-28 Zhe Xu , Menghai Pan , Yuzhong Chen , Huiyuan Chen , Yuchen Yan , Mahashweta Das , Hanghang Tong

Graph alignment, which aims at identifying corresponding entities across multiple networks, has been widely applied in various domains. As the graphs to be aligned are usually constructed from different sources, the inconsistency issues of…

Databases · Computer Science 2023-04-21 Jianheng Tang , Weiqi Zhang , Jiajin Li , Kangfei Zhao , Fugee Tsung , Jia Li

Fault-tolerant connectivity labelings are schemes that, given an $n$-vertex graph $G=(V,E)$ and $f\geq 1$, produce succinct yet informative labels for the elements of the graph. Given only the labels of two vertices $u,v$ and of the…

Data Structures and Algorithms · Computer Science 2024-02-20 Asaf Petruschka , Shay Sapir , Elad Tzalik

For a fixed finite collection of graphs ${\cal F}$, the ${\cal F}$-M-DELETION problem asks, given an $n$-vertex input graph $G,$ for the minimum number of vertices that intersect all minor models in $G$ of the graphs in ${\cal F}$. by…

Data Structures and Algorithms · Computer Science 2021-03-12 Julien Baste , Ignasi Sau , Dimitrios M. Thilikos

Given an n-vertex graph G, a drawing of G in the plane is a mapping of its vertices into points of the plane, and its edges into continuous curves, connecting the images of their endpoints. A crossing in such a drawing is a point where two…

Data Structures and Algorithms · Computer Science 2010-10-20 Julia Chuzhoy , Yury Makarychev , Anastasios Sidiropoulos

The claw finding problem has been studied in terms of query complexity as one of the problems closely connected to cryptography. For given two functions, f and g, as an oracle which have domains of size N and M (N<=M), respectively, and the…

Quantum Physics · Physics 2011-06-17 Seiichiro Tani

This study poses the feature correspondence problem as a hypergraph node labeling problem. Candidate feature matches and their subsets (usually of size larger than two) are considered to be the nodes and hyperedges of a hypergraph. A…

Computer Vision and Pattern Recognition · Computer Science 2011-07-14 Toufiq Parag , Vladimir Pavlovic , Ahmed Elgammal

Graph neural networks (GNNs) have become increasingly popular for classification tasks on graph-structured data. Yet, the interplay between graph topology and feature evolution in GNNs is not well understood. In this paper, we focus on…

Machine Learning · Computer Science 2023-10-27 Vignesh Kothapalli , Tom Tirer , Joan Bruna