Low-rank matrix completion by variational sparse Bayesian learning

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2011, Pages 2188-2191

  Babacan, S Derin ^a   Luessi, Martin ^b   Molina, Rafael ^c   Katsaggelos, Aggelos K ^b  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b Northwestern University   (United States)

^c UNIVERSITY OF GRANADA   (Spain)

Author keywords

automatic relevance determination; Bayesian methods; Low rank matrix completion

Indexed keywords

AUTOMATIC RELEVANCE DETERMINATION; BAYESIAN METHODS; EMPIRICAL RESULTS; LOW-RANK MATRICES; MATRIX FACTORIZATIONS; NUMBER OF METHODS; RECOVERY ALGORITHMS; RECOVERY PERFORMANCE; SPARSE BAYESIAN LEARNING; SPARSITY CONSTRAINTS; STATE-OF-THE-ART METHODS;

RECOVERY; SIGNAL PROCESSING; SPEECH COMMUNICATION;

BAYESIAN NETWORKS;

EID: 80051617844     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2011.5946762     Document Type: Conference Paper

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