Reviews: List-decodable Linear Regression

Post-rebuttal response: I read the authors' response and don't have any further comments. This paper considers the model of "robust statistics" where an alpha fraction of the training data comes from the ground truth distribution while the rest are corrupted arbitrarily (i.e. Traditionally, research has been on the setting where alpha is large, so that the parameters of the true distribution are information-theoretically identifiable. However, recent focus has been on the small alpha setting. Here, the parameters of the true distribution cannot be uniquely identified even with infinitely many samples.