High Dimensional Robust Sparse Regression
@inproceedings{Liu2020HighDR, title={High Dimensional Robust Sparse Regression}, author={L. Liu and Yanyao Shen and Tianyang Li and C. Caramanis}, booktitle={AISTATS}, year={2020} }
We provide a novel -- and to the best of our knowledge, the first -- algorithm for high dimensional sparse regression with constant fraction of corruptions in explanatory and/or response variables. Our algorithm recovers the true sparse parameters with sub-linear sample complexity, in the presence of a constant fraction of arbitrary corruptions. Our main contribution is a robust variant of Iterative Hard Thresholding. Using this, we provide accurate estimators: when the covariance matrix in… CONTINUE READING
Supplemental Presentations
27 Citations
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