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Título:
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Matrix completion of noisy graph signals via proximal gradient minimization
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Autor/a:
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Giménez Febrer, Pedro Juan; Pagès Zamora, Alba Maria
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Otros autores:
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Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions |
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Abstract:
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Abstract:
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This paper takes on the problem of recovering the missing entries of an incomplete matrix, which is known as matrix completion, when the columns of the matrix are signals that lie on a graph and the available observations are noisy. We solve a version of the problem regularized with the Laplacian quadratic form by means of the proximal gradient method, and derive theoretical bounds on the recovery error. Moreover, in order to speed up the convergence of the proximal gradient, we propose an initialization method that utilizes the structural information contained in the Laplacian matrix of the graph. |
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Abstract:
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Peer Reviewed |
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Materia(s):
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-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal
-Signal processing
-Harmonic functions
-Matrix completion
-Signal processing on graphs
-Proximal gradient
-Tractament del senyal
-Funcions harmòniques |
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Derechos:
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Tipo de documento:
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Artículo - Versión presentada
Objeto de conferencia |
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Editor:
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Institute of Electrical and Electronics Engineers (IEEE)
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