Hermitian matrices for clustering directed graphs: insights and applications
<p style="text-align:justify;"> Graph clustering is a basic technique in data mining, and has widespread applications in different domains. While spectral techniques have been successfully applied for clustering undirected graphs, the performance of spectral clustering algorithms fo...
Main Author: | Cucuringu, M |
---|---|
Format: | Working paper |
Published: |
2019
|
Similar Items
-
Hermitian Laplacian Matrix of Directed Graphs
by: LIU Kaiwen, HUANG Zengfeng
Published: (2023-01-01) -
Universality classes of non-Hermitian random matrices
by: Ryusuke Hamazaki, et al.
Published: (2020-06-01) -
Degeneracies and symmetry breaking in pseudo-Hermitian matrices
by: Abhijeet Melkani
Published: (2023-04-01) -
Hermitian matrices of roots of unity and their characteristic polynomials
by: Greaves, Gary Royden Watson, et al.
Published: (2023) -
Hermitian-Randić matrix and Hermitian-Randić energy of mixed graphs
by: Yong Lu, et al.
Published: (2017-03-01)