Reviews: Iterative Least Trimmed Squares for Mixed Linear Regression

This paper studies mixed linear regression and give a number of results. Under various deterministic conditions, they show that given a sufficiently warm start, iterative trimmed least squares converges to the true directions quickly. Their algorithm continues to work in the presence of adversarial corruptions. However the warm start is required to be quite close to the true solution. They give an SVD based initialization procedure that works in the non-noisy setting and when the examples come from a gaussian distribution.