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We consider statistical as well as algorithmic aspects of solving large-scale least-squares (LS) problems using randomized sketching algorithms.
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Low-distortion subspace embeddings in input-sparsity time and applications to robust linear regression
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OSNAP: Faster numerical linear algebra algorithms via sparser subspace embeddings
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Fast ridge regression with randomized principal component analysis and gradient descent
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A statistical perspective on algorithmic leveraging
P. Ma, M. W. Mahoney, and B. Yu · 2014
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Fast approximation of matrix coherence and statistical leverage
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