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- Publisher Website: 10.1016/j.jfranklin.2017.07.001
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Article: Multiple graphs clustering by gradient flow method
Title | Multiple graphs clustering by gradient flow method |
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Authors | |
Issue Date | 2018 |
Citation | Journal of the Franklin Institute, 2018, v. 355, n. 4, p. 1819-1845 How to Cite? |
Abstract | © 2017 The core issue of multiple graphs clustering is to find clusters of vertices from graphs such that these clusters are well-separated in each graph and clusters are consistent across different graphs. The problem can be formulated as a multiple orthogonality constrained optimization model which can be shown to be a relaxation of a multiple graphs cut problem. The resulting optimization problem can be solved by a gradient flow iterative method. The convergence of the proposed iterative scheme can be established. Numerical examples are presented to demonstrate the effectiveness of the proposed method for solving multiple graphs clustering problems in terms of clustering accuracy and computational efficiency. |
Persistent Identifier | http://hdl.handle.net/10722/276569 |
ISSN | 2023 Impact Factor: 3.7 2023 SCImago Journal Rankings: 1.191 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zhu, Hong | - |
dc.contributor.author | Chen, Chuan | - |
dc.contributor.author | Liao, Li Zhi | - |
dc.contributor.author | Ng, Michael K. | - |
dc.date.accessioned | 2019-09-18T08:34:00Z | - |
dc.date.available | 2019-09-18T08:34:00Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Journal of the Franklin Institute, 2018, v. 355, n. 4, p. 1819-1845 | - |
dc.identifier.issn | 0016-0032 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276569 | - |
dc.description.abstract | © 2017 The core issue of multiple graphs clustering is to find clusters of vertices from graphs such that these clusters are well-separated in each graph and clusters are consistent across different graphs. The problem can be formulated as a multiple orthogonality constrained optimization model which can be shown to be a relaxation of a multiple graphs cut problem. The resulting optimization problem can be solved by a gradient flow iterative method. The convergence of the proposed iterative scheme can be established. Numerical examples are presented to demonstrate the effectiveness of the proposed method for solving multiple graphs clustering problems in terms of clustering accuracy and computational efficiency. | - |
dc.language | eng | - |
dc.relation.ispartof | Journal of the Franklin Institute | - |
dc.title | Multiple graphs clustering by gradient flow method | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.jfranklin.2017.07.001 | - |
dc.identifier.scopus | eid_2-s2.0-85039795278 | - |
dc.identifier.volume | 355 | - |
dc.identifier.issue | 4 | - |
dc.identifier.spage | 1819 | - |
dc.identifier.epage | 1845 | - |
dc.identifier.isi | WOS:000426986200016 | - |
dc.identifier.issnl | 0016-0032 | - |