NeurIPS 2020Poster
Online Robust Regression via SGD on the l1 loss
作者: Scott Pesme, Nicolas Flammarion
摘要
We consider the robust linear regression problem in the online setting where we have access to the data in a streaming manner, one data point after the other. More specifically, for a true parameter $ \theta^* $, we consider the corrupted Gaussian linear model $y =