Tensor completion for estimating missing values in visual data

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 35, Issue 1, 2013, Pages 208-220

  Liu, Ji ^a   Musialski, Przemyslaw ^b   Wonka, Peter ^c,d   Ye, Jieping ^e  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b VRVIS RESEARCH CENTER   (Austria)

^c Department of Chemistry and Biochemistry   (United States)

^d KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Saudi Arabia)

^e ARIZONA STATE UNIVERSITY   (United States)

Author keywords

sparse learning; Tensor completion; trace norm

Indexed keywords

ACQUISITION PROCESS; ALTERNATING DIRECTION METHODS; CONVEX OPTIMIZATION PROBLEMS; COORDINATE DESCENT; HEURISTIC APPROACH; HIGH-ACCURACY; LOW RANK; MATRIX CASE; MATRIX COMPLETION; MATRIX TRACE; MINIMIZATION PROBLEMS; MISSING VALUES; MULTIPLE CONSTRAINT; NON-SMOOTH; OPTIMAL SOLUTIONS; POTENTIAL APPLICATIONS; QUANTITATIVE EVALUATION; RELAXATION TECHNIQUES; SPARSE LEARNING; TENSOR COMPLETION; TRACE-NORMS; VISUAL DATA;

ALGORITHMS; CONVEX OPTIMIZATION; HEURISTIC METHODS; MATRIX ALGEBRA;

TENSORS;

ARTICLE; ARTIFACT; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; METHODOLOGY; SAMPLE SIZE; SIGNAL PROCESSING;

ARTIFACTS; ARTIFICIAL INTELLIGENCE; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; SAMPLE SIZE; SIGNAL PROCESSING, COMPUTER-ASSISTED;

MLCS; MLOWN;

EID: 84870175618     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2012.39     Document Type: Article

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