A Majorization-Minimization Gauss-Newton Method for 1-Bit Matrix Completion

arXiv:2304.13940v2 Announce Type: replace-cross
Abstract: In 1-bit matrix completion, the aim is to estimate an underlying low-rank matrix from a partial set of binary observations. We propose a novel method for 1-bit matrix completion called MMGN. Our method is based on the majorization-minimization (MM) principle, which converts the original optimization problem into a sequence of standard low-rank matrix completion problems. We solve each of these sub-problems by a factorization approach that explicitly enforces the assumed low-rank structure and then apply …

abstract aim arxiv binary cs.lg gauss low matrix novel optimization set stat.ml type