Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks

Neural Information Processing Systems 

The classical iteratively reweighted least-squares (IRLS) algorithm aims to recover an unknown signal from linear measurements by performing a sequence of weighted least squares problems, where the weights are recursively updated at each step.