Tensor Completion Algorithms in Big Data Analytics
نویسندگان
چکیده
منابع مشابه
Tensor Completion Algorithms in Big Data Analytics
Tensor completion is a problem of lling the missing or unobserved entries of partially observed tensors. Due to the multidimensional character of tensors in describing complex datasets, tensor completion algorithms and their applications have received wide aention and achievement in data mining, computer vision, signal processing, and neuroscience, etc. In this survey, we provide a modern ove...
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Abstract. In the tensor completion problem, one seeks to estimate a low-rank tensor based on a random sample of revealed entries. In terms of the required sample size, earlier work revealed a large gap between estimation with unbounded computational resources (using, for instance, tensor nuclear norm minimization) and polynomial-time algorithms. Among the latter, the best statistical guarantees...
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ژورنال
عنوان ژورنال: ACM Transactions on Knowledge Discovery from Data
سال: 2019
ISSN: 1556-4681,1556-472X
DOI: 10.1145/3278607