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Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression
[article]
2019
arXiv
pre-print
We study the problem of robust linear regression with response variable corruptions. We consider the oblivious adversary model, where the adversary corrupts a fraction of the responses in complete ignorance of the data. We provide a nearly linear time estimator which consistently estimates the true regression vector, even with 1-o(1) fraction of corruptions. Existing results in this setting either don't guarantee consistent estimates or can only handle a small fraction of corruptions. We also
arXiv:1903.08192v1
fatcat:pyqsvm467rg5vcilbjbt5kdw6q