Partial Hard Thresholding: Towards A Principled Analysis of Support Recovery

In machine learning and compressed sensing, it is of central importance to understand when a tractable algorithm recovers the support of a sp arse signal from its compressed measurements. In this paper, we present a princi pled analysis on the support recovery performance for a family of hard threshold ing algorithms. To this end, we appeal to the partial hard thresholding (PHT) op erator proposed recently by Jain et al. [IEEE Trans.