Alternating Direction Method of Multipliers for Generalized Low-Rank Tensor Recovery

Abstract

Abstract: Low-Rank Tensor Recovery (LRTR), the higher order generalization of Low-Rank Matrix Recovery (LRMR), is especially suitable for analyzing multi-linear data with gross corruptions, outliers and missing values, and it attracts broad attention in the fields of computer vision, machine learning and data mining. This paper considers a generalized model… (More)
DOI: 10.3390/a9020028

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