SS-SIPTM-1.1

NODE CLUSTERING OF TIME-VARYING GRAPHS BASED ON TEMPORAL LABEL SMOOTHNESS

Katsuki Fukumoto, Koki Yamada, Yuichi Tanaka, Tokyo University of Agriculture and Technology, Japan
Session:
Signal Processing and Machine Learning over Graphs
Track:
Signal and Information Processing Theory and Methods (SIPTM)
Session Time:
Thu, 16 Dec, 14:00 - 16:00 Japan Standard Time (UTC +9)
Thu, 16 Dec, 05:00 - 07:00 Coordinated Universal Time
Thu, 16 Dec, 00:00 - 02:00 Eastern Standard Time (UTC -5)
Wed, 15 Dec, 21:00 - 23:00 Pacific Standard Time (UTC -8)
Session Co-Chairs:
Yuichi Tanaka, Tokyo University of Agriculture and Technology and Shunsuke Ono, Tokyo Institute of Technology
Presentation
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Session SS-SIPTM-1
TH2.LS-B.1: NODE CLUSTERING OF TIME-VARYING GRAPHS BASED ON TEMPORAL LABEL SMOOTHNESS
Katsuki Fukumoto, Koki Yamada, Yuichi Tanaka, Tokyo University of Agriculture and Technology, Japan
TH2.LS-B.2: Recovery of Time Series of Graph Signals Over Dynamic Topology
Eisuke Yamagata, Shunsuke Ono, Tokyo Institute of Technology, Japan
TH2.LS-B.3: AN EMPIRICAL STUDY ON COMPRESSED DECENTRALIZED STOCHASTIC GRADIENT ALGORITHMS WITH OVERPARAMETERIZED MODELS
Arjun Ashok Rao, Hoi-To Wai, The Chinese University of Hong Kong, Hong Kong
TH2.LS-B.4: Model Selection-inspired Coefficients Optimization for Polynomial-Kernel Graph Learning
Cheng Yang, Guangtao Zhai, Shanghai Jiao Tong University, China; Fen Wang, Minxiang Ye, Zhejiang Lab, China; Xiao-Ping Zhang, Ryerson University, Canada; Vladimir Stankovic, Lina Stankovic, University of Strathclyde, United Kingdom of Great Britain and Northern Ireland
TH2.LS-B.5: CHANNEL-WISE EARLY STOPPING WITHOUT A VALIDATION SET VIA NNK POLYTOPE INTERPOLATION
David Bonet, Javier Ruiz-Hidalgo, Universitat Politècnica de Catalunya, Spain; Antonio Ortega, Sarath Shekkizhar, University of Southern California, United States of America