# A statistical perspective of sampling scores for linear regression

@article{Chen2016ASP,
title={A statistical perspective of sampling scores for linear regression},
author={Siheng Chen and R. Varma and Aarti Singh and J. Kovacevic},
journal={2016 IEEE International Symposium on Information Theory (ISIT)},
year={2016},
pages={1556-1560}
}
• Siheng Chen, +1 author J. Kovacevic
• Published 2016
• Mathematics, Computer Science
• 2016 IEEE International Symposium on Information Theory (ISIT)
In this paper, we consider a statistical problem of learning a linear model from noisy samples. Existing work has focused on approximating the least squares solution by using leverage-based scores as an importance sampling distribution. However, no finite sample statistical guarantees and no computationally efficient optimal sampling strategies have been proposed. To evaluate the statistical properties of different sampling strategies, we propose a simple yet effective estimator, which is easy… Expand
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