Minimax Lower Bounds for Noisy Matrix Completion Under Sparse Factor Models
نویسندگان
چکیده
منابع مشابه
Minimax Lower Bounds for Noisy Matrix Completion Under Sparse Factor Models
This paper examines fundamental error characteristics for a general class of matrix completion problems, where matrix of interest is a product of two a priori unknown matrices, one of which is sparse, and the observations are noisy. Our main contributions come in the form of minimax lower bounds for the expected per-element squared error for these problems under several noise/corruption models;...
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ژورنال
عنوان ژورنال: IEEE Transactions on Information Theory
سال: 2018
ISSN: 0018-9448,1557-9654
DOI: 10.1109/tit.2018.2809782