Searching for authors named "Luis Rademacher" – sorted by Relevance.
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Matrix approximation and projective clustering via volume sampling
- We present two new results for the problem of approximating a given real m × n matrix A by a rank-k matrix D, where k < min{m, n}, so as to minimize ||A − D| | 2 F. It is known that by sampling O(k/ɛ) rows of the matrix, one can find a low-rank approximation with additive error ɛ||A| | 2 F. Our firs
- Cited by 29 (2 self) – Add To MetaCart
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Amit Sinha and Anantha Chandrakasan. Energy Efficient Real-Time Scheduling
- Abstract: Frieze, Kannan, and Vempala (JACM 2004) proved that a small sample of rows of a given matrix A spans the rows of a low-rank approximation D that minimizes �A−D�F within a small additive error, and the sampling can be done efficiently using just two passes over the matrix. In this paper, we
- Cited by 1 (0 self) – Add To MetaCart

