Simultaneous Tensor Decomposition and Completion Using Factor Priors

The success of research on matrix completion is evident in a variety of real-world applications. Tensor completion, which is a high-order extension of matrix completion, has also generated a great deal of research interest in recent years. Given a tensor with incomplete entries, existing methods use...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence Jg. 36; H. 3; S. 577 - 591
Hauptverfasser:	Yi-Lei Chen, Chiou-Ting Hsu, Liao, Hong-Yuan Mark
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Los Alamitos, CA IEEE 01.03.2014 IEEE Computer Society The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Applied sciences Approximation methods Artificial intelligence Brain modeling Computer science; control theory; systems Connectionism. Neural networks Convergence Decomposition Effectiveness Equations Exact sciences and technology factor priors Factorization Mathematical analysis Mathematical model Mathematical models Matrix decomposition multilinear model analysis Pattern recognition. Digital image processing. Computational geometry Tasks Tensile stress Tensor completion Tensors Tucker decomposition Visualization Computer vision Data analysis Adaptive resonance theory Minimization Modeling multilinear model analysis Missing data Tensor completion Completeness Factorization method factor priors Tucker decomposition Tensor method Synthetic data
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
Online-Zugang:	Volltext
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