Noisy low-rank matrix completion with general sampling distribution
نویسندگان
چکیده
منابع مشابه
Noisy low-rank matrix completion with general sampling distribution
In the present paper we consider the problem of matrix completion with noise for general sampling schemes. Unlike previous works, in our construction we do not need to know or to evaluate the sampling distribution or the variance of the noise. We propose new nuclear-norm penalized estimators, one of them of the “square-root” type. We prove that, up to a logarithmic factor, our estimators achiev...
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While datasets are frequently represented as matrices, real-word data is imperfect and entries are often missing. In many cases, the data are very sparse and the matrix must be filled in before any subsequent work can be done. This optimization problem, known as matrix completion, can be made well-defined by assuming the matrix to be low rank. The resulting rank-minimization problem is NP-hard,...
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ژورنال
عنوان ژورنال: Bernoulli
سال: 2014
ISSN: 1350-7265
DOI: 10.3150/12-bej486