Robust and Sparse Estimation of Linear Regression Coefficients with Heavy-tailed Noises and Covariates. (arXiv:2206.07594v1 [stat.ML])

Web: http://arxiv.org/abs/2206.07594

Robust and sparse estimation of linear regression coefficients is
investigated. The situation addressed by the present paper is that covariates
and noises are sampled from heavy-tailed distributions, and the covariates and
noises are contaminated by malicious outliers. Our estimator can be computed
efficiently. Further, our estimation error bound is sharp.

arxiv linear linear regression ml regression