support recovery of greedy block coordinate descent using the near orthogonality property
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ID: 187451
2017
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Abstract
In this paper, using the near orthogonal property, we analyze the performance of greedy block coordinate descent (GBCD) algorithm when both the measurements and the measurement matrix are perturbed by some errors. An improved sufficient condition is presented to guarantee that the support of the sparse matrix is recovered exactly. A counterexample is provided to show that GBCD fails. It improves the existing result. By experiments, we also point out that GBCD is robust under these perturbations.
| Reference Key |
li2017mathematicalsupport
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|---|---|
| Authors | ;Haifeng Li |
| Journal | journal of power sources |
| Year | 2017 |
| DOI |
10.1155/2017/4903791
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| URL | |
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