Adaptive Sampling and Fast Low-Rank Matrix Approximation-Reference-Cited by-同舟云学术

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Adaptive Sampling and Fast Low-Rank Matrix Approximation

Published:2006 Issue: Volume: Page:292-303
ISSN:0302-9743
Container-title:Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
language:
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Author:

Deshpande Amit,Vempala Santosh

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/11830924_28.pdf

Reference16 articles.

1. Lecture Notes in Computer Science;S. Arora,2006

2. Achlioptas, D., McSherry, F.: Fast Computation of Low Rank Approximations. In: Proceedings of the 33rd Annual Symposium on Theory of Computing (2001)

3. Aggarwal, C., Procopiuc, C., Wolf, J., Yu, P., Park, J.: Fast Algorithms for Projected Clustering. In: Proceedings of SIGMOD (1999)

4. Bar-Yosseff, Z.: Sampling Lower Bounds via Information Theory. In: Proceedings of the 35th Annual Symposium on Theory of Computing (2003)

5. de la Vega, W.F., Karpinski, M., Kenyon, C., Rabani, Y.: Approximation schemes for clustering problems. In: Proceedings of the 35th Annual ACM Symposium on Theory of Computing (2003)

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