Discrete Aware Matrix Completion via Convexized $\ell_0$-Norm Approximation

arXiv:2405.02101v1 Announce Type: cross
Abstract: We consider a novel algorithm, for the completion of partially observed low-rank matrices in a structured setting where each entry can be chosen from a finite discrete alphabet set, such as in common recommender systems. The proposed low-rank matrix completion (MC) method is an improved variation of state-of-the-art (SotA) discrete aware matrix completion method which we previously proposed, in which discreteness is enforced by an $\ell_0$-norm regularizer, not by replaced with the $\ell_1$-norm, but instead …

abstract algorithm alphabet approximation arxiv cs.lg eess.sp low matrix norm novel recommender systems set systems type variation via