Robust Partially-Compressed Least-Squares
THIRTY-FIRST AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, pp. 1742-1748, 2017.
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 tradeoff. In this paper, we investigate compressed least...More
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