Robust Method for Network Topology Identification Under Structural Equation Model

We present a robust method to infer network topology in the presence of outliers from given observations at nodes under the structural equation model. We introduce auxiliary matrices modeling Gaussian noise and sparse outliers. The topology identification task is cast as a minimization problem of th...

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Veröffentlicht in:	2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP) S. 1 - 6
Hauptverfasser:	Yoshida, Kohei, Yukawa, Masahiro
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 22.09.2024
Schlagworte:	graph learning Mathematical models Minimization methods Network topology operator splitting algorithm outlier robustness Pollution measurement Robustness Signal processing algorithms Simulation Sparse matrices structural equation model Topology Vectors
ISSN:	2161-0371
Online-Zugang:	Volltext
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