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• W2325477568 startingPage "637" @default.
• W2325477568 abstract "The completion of matrices with missing values under the rank constraint is a nonconvex optimization problem. A popular convex relaxation is based on minimization of the nuclear norm (sum of singular values) of the matrix. For this relaxation, an important question is whether the two optimization problems lead to the same solution. This question was addressed in the literature mostly in the case of random positions of missing elements and random known elements. In this contribution, we analyze the case of structured matrices with a fixed pattern of missing values, namely, the case of Hankel matrix completion. We extend existing results on completion of rank-one real Hankel matrices to completion of rank-r complex Hankel matrices." @default.
• W2325477568 created "2016-06-24" @default.
• W2325477568 creator A5033972557 @default.
• W2325477568 creator A5048869483 @default.
• W2325477568 date "2016-06-01" @default.
• W2325477568 modified "2023-10-18" @default.
• W2325477568 title "Hankel Low-Rank Matrix Completion: Performance of the Nuclear Norm Relaxation" @default.
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• W2325477568 doi "https://doi.org/10.1109/jstsp.2016.2535182" @default.
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