Empirical Bayes Matrix Completion
Machine Learning
2019-04-10 v2 Statistics Theory
Methodology
Statistics Theory
Abstract
We develop an empirical Bayes (EB) algorithm for the matrix completion problems. The EB algorithm is motivated from the singular value shrinkage estimator for matrix means by Efron and Morris (1972). Since the EB algorithm is essentially the EM algorithm applied to a simple model, it does not require heuristic parameter tuning other than tolerance. Numerical results demonstrated that the EB algorithm achieves a good trade-off between accuracy and efficiency compared to existing algorithms and that it works particularly well when the difference between the number of rows and columns is large. Application to real data also shows the practical utility of the EB algorithm.
Cite
@article{arxiv.1706.01252,
title = {Empirical Bayes Matrix Completion},
author = {Takeru Matsuda and Fumiyasu Komaki},
journal= {arXiv preprint arXiv:1706.01252},
year = {2019}
}
Comments
15 pages