Efficient Algorithms for Outlier-Robust Regression

COLT, pp. 1420-1430, 2018.

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Abstract:

We give the first polynomial-time algorithm for performing linear or polynomial regression resilient to adversarial corruptions in both examples and labels. Given a sufficiently large (polynomial-size) training set drawn iid from distribution (D) and subsequently corrupted on some fraction of points, our algorithm outputs a linear functio...More

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