Structural Conditions for Projection-Cost Preservation via Randomized Matrix Multiplication

29 May 2017 Agniva Chowdhury Jiasen Yang Petros Drineas

Projection-cost preservation is a low-rank approximation guarantee which ensures that the cost of any rank-$k$ projection can be preserved using a smaller sketch of the original data matrix. We present a general structural result outlining four sufficient conditions to achieve projection-cost preservation... (read more)

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