ABSTRACT
The problem of reconstructing large-scale matrices from incomplete and noisy observations has attracted a lot of attention in recent years. Of particular interest is the reconstruction or completion of low-rank matrices, which finds many practical applications in recommender systems, collaborative filtering, system identification, and video surveillance.
