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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-13 14:30 |
Okinawa |
Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
Study on Evaluating the Effectiveness of Graph Summarization for Sampling Graphs Ryotaro Matsuo, Ryo Nakamura (Fukuoka Univ.) CQ2023-75 |
In recent years, a compact graph representation called {em summary graph} has been extensively studied. This representa... [more] |
CQ2023-75 pp.26-31 |
SIP, SP, EA, IPSJ-SLP [detail] |
2024-02-29 16:20 |
Okinawa |
(Primary: On-site, Secondary: Online) |
EA2023-77 SIP2023-124 SP2023-59 |
In this paper, we consider a dynamic sensor placement problem where sensors can move within a network over time. Sensor ... [more] |
EA2023-77 SIP2023-124 SP2023-59 pp.97-102 |
IN, IA (Joint) |
2023-12-21 12:30 |
Hiroshima |
Satellite Campus Hiroshima |
[Short Paper]
A Study on the Importance of Spectral Representation of Subgraphs with Different Sampling Strategies Koki Kato, Ryo Nakamura (Fukuoka Univ.) IA2023-43 |
Spectral graph theory has been actively studied to analyze topological property of networks using eigenvalues and eigenv... [more] |
IA2023-43 pp.1-4 |
IN, IA (Joint) |
2023-12-21 15:55 |
Hiroshima |
Satellite Campus Hiroshima |
[Short Paper]
Study on the Effectiveness of Graph Summarization Methods for Sampling Graphs Hirosato Ito, Ryotaro Matsuo, Ryo Nakamura (Fukuoka Univ.) IA2023-46 |
In general, it is not trivial to obtain various large-scale graphs with graph structures such as communication networks ... [more] |
IA2023-46 pp.17-19 |
IN, IA (Joint) |
2023-12-22 15:00 |
Hiroshima |
Satellite Campus Hiroshima |
[Short Paper]
A Study on the Applicability of Graph Reduction to Evaluating the Robustness of Complex Networks Murakawa Yamato, Ryotaro Matsuo, Ryo Nakamura (Fukuoka Univ.) IA2023-53 |
Generally, the computational complexity of network simulation and machine learning based on graph structure such as GNN ... [more] |
IA2023-53 pp.48-52 |
EA, US, SP, SIP, IPSJ-SLP [detail] |
2021-03-03 10:50 |
Online |
Online |
Design of Graph Signal Sampling Matrices for Arbitrary Signal Subspaces Junya Hara, Koki Yamada (TUAT), Shunsuke Ono (TIT), Yuichi Tanaka (TUAT) EA2020-61 SIP2020-92 SP2020-26 |
We propose a design method of sampling matrices for graph signals that guarantees perfect recovery for arbitrary graph s... [more] |
EA2020-61 SIP2020-92 SP2020-26 pp.9-14 |
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