# Robust Estimation via Robust Gradient Estimation

@article{Prasad2018RobustEV,
title={Robust Estimation via Robust Gradient Estimation},
author={A. Prasad and Arun Sai Suggala and Sivaraman Balakrishnan and Pradeep Ravikumar},
journal={ArXiv},
year={2018},
volume={abs/1802.06485}
}
We provide a new computationally-efficient class of estimators for risk minimization. We show that these estimators are robust for general statistical models: in the classical Huber epsilon-contamination model and in heavy-tailed settings. Our workhorse is a novel robust variant of gradient descent, and we provide conditions under which our gradient descent variant provides accurate estimators in a general convex risk minimization problem. We provide specific consequences of our theory for… Expand
128 Citations

#### References

SHOWING 1-10 OF 56 REFERENCES
Variance-based Regularization with Convex Objectives
• Computer Science, Mathematics
• NIPS
• 2017
Loss Minimization and Parameter Estimation with Heavy Tails
• Mathematics, Computer Science
• J. Mach. Learn. Res.
• 2016
Self Scaled Regularized Robust Regression
• Mathematics, Computer Science
• 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
• 2015