  We analyse the pruning procedure behind the lottery ticket hypothesis
arXiv:1803.03635v5, iterative magnitude pruning (IMP), when applied to linear
models trained by gradient flow. We begin by presenting sufficient conditions
on the statistical structure of the features under which IMP prunes those
features that have smallest projection onto the data. Following this, we
explore IMP as a method for sparse estimation.
