On learning sparse linear models from cross samples

Mina Sadat Mahmoudi, Seyed Abolfazl Motahari, Babak Hossein Khalaj

Abstract: Highlights•A specific dependency among samples has been theoretically and numerically studied.•This dependency occurs in the study of cancer drug response and movie recommendation.•Lasso estimation error using such samples shows a phase-transition behavior.•The transition threshold seems to be governed by sparsity level of the true parameter vector.•If the sample size is large enough, dependent samples are as useful as i.i.d. samples.