Spectral Graph Matching and Regularized Quadratic Relaxations I Algorithm and Gaussian Analysis

Graph matching aims at finding the vertex correspondence between two unlabeled graphs that maximizes the total edge weight correlation. This amounts to solving a computationally intractable quadratic assignment problem. In this paper, we propose a new spectral method, graph matching by pairwise eige...

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Veröffentlicht in:	Foundations of computational mathematics Jg. 23; H. 5; S. 1511 - 1565
Hauptverfasser:	Fan, Zhou, Mao, Cheng, Wu, Yihong, Xu, Jiaming
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.10.2023 Springer Nature B.V
Schlagworte:	Algorithms Apexes Applications of Mathematics Assignment problem Computer Science Correlation coefficients Economics Eigenvalues Eigenvectors Graph matching Graph theory Graphs Linear and Multilinear Algebras Math Applications in Computer Science Mathematics Mathematics and Statistics Matrix Theory Numerical Analysis Operations research Polynomials Quadratic programming Similarity Spectral methods Statistical analysis Random matrix theory Convex relaxations Primary 90C25 Quadratic assignment problem Quadratic programming Secondary 68Q87 Spectral methods Graph matching
ISSN:	1615-3375, 1615-3383
Online-Zugang:	Volltext
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