5b69b9cb83065d403869739ae7f0995e-Reviews.html

Review of "Low-rank matrix reconstruction and clustering" This paper contributes a new algorithm for low-rank matrix reconstruction which is based on an application of Belief Propagation (BP) message-passing to a Bayesian model of the reconstruction problem. The algorithm, as described in the "Supplementary Material", incorporates two simplifying approximations, based on assuming a large number of rows and columns, respectively, in the input matrix. The algorithm is evaluated in a novel manner against Lloyd's K-means algorithm by formulating clustering as a matrix reconstruction problem. It is also compared against Variational Bayes Matrix Factorization (VBMF), which seems to be the only previous message-passing reconstruction algorithm. Cons There are some arguments against accepting the paper.