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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 6 of 6  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
CQ 2023-07-12
14:00		 Hokkaido
(Primary: On-site, Secondary: Online)		 Study on the Effectiveness of Matrix Approximation without Rank Constraint
Eriko Segawa, Yusuke Sakumto (Kwansei Gakuin Univ.) CQ2023-10		 The proper selection of graph spectrum is crucial for constructing efficient graph algorithms. We have discussed a matri... [more] CQ2023-10
pp.12-17
IMQ, IE, MVE, CQ
(Joint) [detail]		 2023-03-15
11:00		 Okinawa Okinawaken Seinenkaikan (Naha-shi)
(Primary: On-site, Secondary: Online)		 Evaluating the Efficiency of Anomaly Detection Methods for Temporal Networks Using the Graph Spectrum
Masataka Nagao, Eriko Segawa, Yusuke Sakumoto (Kwansei Gakuin Univ.) CQ2022-83		 LAD (Laplacian Anomaly Detection) is a method for detecting anomalies in dynamic networks using the eigenvalues (the gra... [more] CQ2022-83
pp.19-24
IMQ, IE, MVE, CQ
(Joint) [detail]		 2023-03-15
11:25		 Okinawa Okinawaken Seinenkaikan (Naha-shi)
(Primary: On-site, Secondary: Online)		 Study on the Importance of Each Eigenvalue and Eigenvector for Laplacian Matrix Using Matrix Approximation
Eriko Segawa, Yusuke Sakumoto (Kwansei Gakuin Univ.) CQ2022-84		 It is important for developing sophisticated graph algorithms to understand deeply the characteristics of the typical ma... [more] CQ2022-84
pp.25-30
IN, IA
(Joint)		 2022-12-13
10:15		 Hiroshima Higashi-Senda campus, Hiroshima Univ.
(Primary: On-site, Secondary: Online)		 [Short Paper] Investigation of a Matrix Approximation Method for Analyzing the Information Amount Contained in the Specified Eigenvalues and Eigenvectors
Eriko Segawa, Yusuke Sakumoto (Kwansei Gakuin Univ) IA2022-56		 In general, the large eigenvalues and their eigenvectors of a matrix representing the network structure are important to... [more] IA2022-56
pp.47-49
CQ, CS
(Joint)		 2022-05-12
16:10		 Fukui Fukui (Fuku Pref.)
(Primary: On-site, Secondary: Online)		 Why Do Small Eigenvalues of Laplacian Matrix Improve Anomaly Detection of Temporal Networks?
Eriko Segawa, Yusuke Sakumoto (Kwansei Gakuin Univ.) CQ2022-9		 Many real networks are temporal networks in which the nodes and their relationships change over time, and technology to ... [more] CQ2022-9
pp.44-49
CQ, MIKA
(Joint)		 2021-09-09
10:55		 Online Online Proposal of an Improving Method for the Laplacian Anomaly Detection of Temporal Networks
Eriko Segawa, Toyoaki Taniguchi, Yusuke Sakumoto (Kwansei Gakuin Univ.) CQ2021-40		 Many networks in the real world are dynamic and temporal wherein relationships among nodes change with time. Technologie... [more] CQ2021-40
pp.17-22
 Results 1 - 6 of 6  /   
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