# Robust Partially-Compressed Least-Squares

@article{Becker2017RobustPL, title={Robust Partially-Compressed Least-Squares}, author={Stephen Becker and Ban Kawas and Marek Petrik}, journal={ArXiv}, year={2017}, volume={abs/1510.04905} }

Randomized matrix compression techniques, such as the Johnson-Lindenstrauss transform, have emerged as an effective and practical way for solving large-scale problems efficiently. With a focus on computational efficiency, however, forsaking solutions quality and accuracy becomes the trade-off. In this paper, we investigate compressed least-squares problems and propose new models and algorithms that address the issue of error and noise introduced by compression. While maintaining…

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