NeurIPS 2015poster202 citations
Robust Regression via Hard Thresholding
Kush Bhatia, Prateek Jain, Purushottam Kar
Abstract
We study the problem of Robust Least Squares Regression (RLSR) where several response variables can be adversarially corrupted. More specifically, for a data matrix X \in \R^{p x n} and an underlying model w
BibTeX
@inproceedings{NIPS2015_1be3bc32,
author = {Bhatia, Kush and Jain, Prateek and Kar, Purushottam},
booktitle = {Advances in Neural Information Processing Systems},
editor = {C. Cortes and N. Lawrence and D. Lee and M. Sugiyama and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Robust Regression via Hard Thresholding},
url = {https://proceedings.neurips.cc/paper_files/paper/2015/file/1be3bc32e6564055d5ca3e5a354acbef-Paper.pdf},
volume = {28},
year = {2015}
}