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In this paper, we propose an efficient and scalable low rank matrix completion algorithm. The key idea is to extend the orthogonal matching pursuit method from the vector case to

In this paper, we propose an efficient and scalable low rank matrix completion algorithm. The key idea is to extend the orthogonal matching pursuit method from the vector case to the matrix case. We further propose an economic version of our algorithm by introducing a novel weight updating rule to reduce the time and storage complexity. Both versions are computationally inexpensive for each matrix pursuit iteration and find satisfactory results in a few iterations. Another advantage of our proposed algorithm is that it has only one tunable parameter, which is the rank.

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Date Created
  • 2014-11-30
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  • Text
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    Identifier
    • Digital object identifier: 10.1137/130934271
    • Identifier Type
      International standard serial number
      Identifier Value
      1095-7197
    • Identifier Type
      International standard serial number
      Identifier Value
      1064-8275
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    • Link to published article.

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    Wang, Zheng, Lai, Ming-Jun, Lu, Zhaosong, Fan, Wei, Davulcu, Hasan, & Ye, Jieping (2015). ORTHOGONAL RANK-ONE MATRIX PURSUIT FOR LOW RANK MATRIX COMPLETION. SIAM JOURNAL ON SCIENTIFIC COMPUTING, 37(1). http://dx.doi.org/10.1137/130934271

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