Maximum rank matrix completion

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Maximum rank matrix completion

The maximum rank completion problem is the problem of, given a partial matrix (that is, a matrix where we are only given some of the entries), ll in the unknown entries in such a way as to maximize the rank. Applications include bipartite matching and matroid intersection for linearly represented matroids. We describe an algorithm that nds a maximum rank completion by perturbing an arbitrary co...

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High-Rank Matrix Completion

This paper considers the problem of completing a matrix with many missing entries under the assumption that the columns of the matrix belong to a union of multiple low-rank subspaces. This generalizes the standard low-rank matrix completion problem to situations in which the matrix rank can be quite high or even full rank. Since the columns belong to a union of subspaces, this problem may also ...

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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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Rank-One Matrix Pursuit for Matrix Completion

Low rank matrix completion has been applied successfully in a wide range of machine learning applications, such as collaborative filtering, image inpainting and Microarray data imputation. However, many existing algorithms are not scalable to large-scale problems, as they involve computing singular value decomposition. In this paper, we present an efficient and scalable algorithm for matrix com...

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ژورنال

عنوان ژورنال: Linear Algebra and its Applications

سال: 1999

ISSN: 0024-3795

DOI: 10.1016/s0024-3795(98)10210-0