Large Scale Constrained Linear Regression Revisited: Faster Algorithms via Preconditioning

9 Feb 2018 Di Wang Jinhui Xu

In this paper, we revisit the large-scale constrained linear regression problem and propose faster methods based on some recent developments in sketching and optimization. Our algorithms combine (accelerated) mini-batch SGD with a new method called two-step preconditioning to achieve an approximate solution with a time complexity lower than that of the state-of-the-art techniques for the low precision case... (read more)

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