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Paper Abstract and Keywords
Presentation 2026-07-22 09:00
[Poster Presentation] An Investigation of GCT+GSS for Graph Clustering of Brain Networks
Ippei Noguchi, Chissaki Yoneda, Yusuke Sakumoto (Kwansei Gakuin Univ) CQ2026-25
Abstract (in Japanese) (See Japanese page) 
(in English) Network analysis of brain connectomes is important for understanding brain characteristics and disease mechanisms. By treating brain connectomes as brain networks for individual subjects, it is possible to consider the problem of classifying subjects' states and properties based on differences in network structures. In such brain network classification, it is important to appropriately represent the structural features of each network. GCT~(Geodesic Clustering with Tangent spaces) is a method that represents the subspace spanned by multiple eigenvectors obtained from each network as a point on the Grassmann manifold, and performs clustering based on relationships between subspaces. However, in GCT, clustering performance depends on which eigenvectors are used to construct the subspace, and therefore selecting a subspace effective for network classification is an important issue. GSS~(Graph Spectrum Shift) is an operation that shifts eigenvalues and can change the eigenvectors selected in low-rank approximation. Therefore, this paper studies GCT+GSS, which selects eigenvectors based on low-rank approximation with GSS and determines the subspace used in GCT. In the evaluation, we investigate the clustering accuracy using artificial networks and real brain networks, and evaluate the effectiveness of subspace selection
based on GSS.
Keyword (in Japanese) (See Japanese page) 
(in English) Brain Network / Graph Clustering / Grassmann Manifold / GCT / GSS / Low-Rank Approximation / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 121, CQ2026-25, pp. 67-72, July 2026.
Paper # CQ2026-25 
Date of Issue 2026-07-14 (CQ) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF CQ2026-25

Conference Information
Committee CQ  
Conference Date 2026-07-21 - 2026-07-23 
Place (in Japanese) (See Japanese page) 
Place (in English) Eef Jouhou Plaza 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To CQ 
Conference Code 2026-07-CQ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Investigation of GCT+GSS for Graph Clustering of Brain Networks 
Sub Title (in English)  
Keyword(1) Brain Network  
Keyword(2) Graph Clustering  
Keyword(3) Grassmann Manifold  
Keyword(4) GCT  
Keyword(5) GSS  
Keyword(6) Low-Rank Approximation  
Keyword(7)  
Keyword(8)  
1st Author's Name Ippei Noguchi  
1st Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ)
2nd Author's Name Chissaki Yoneda  
2nd Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ)
3rd Author's Name Yusuke Sakumoto  
3rd Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ)
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Speaker Author-1 
Date Time 2026-07-22 09:00:00 
Presentation Time 60 minutes 
Registration for CQ 
Paper # CQ2026-25 
Volume (vol) vol.126 
Number (no) no.121 
Page pp.67-72 
#Pages 6 
Date of Issue 2026-07-14 (CQ) 

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