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IEEE Trans. Inf. Theory
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Near-optimal coresets for least-squares regression

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Abstract

We study the (constrained) least-squares regression as well as multiple response least-squares regression and ask the question of whether a subset of the data, a coreset, suffices to compute a good approximate solution to the regression. We give deterministic, low-order polynomial-time algorithms to construct such coresets with approximation guarantees, together with lower bounds indicating that there is not much room for improvement upon our results. © 1963-2012 IEEE.

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IEEE Trans. Inf. Theory

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