Optimal Recovery of Missing Values for Non-negative Matrix Factorization
Optimal Recovery of Missing Values for Non-negative Matrix Factorization
Abstract We extend the approximation-theoretic technique of optimal recovery to the setting of imputing missing values in clustered data, specifically for non-negative matrix factorization (NMF), and develop an implementable algorithm. Under certain geometric conditions, we prove tight upper bounds on NMF relative error, which is the first bound of this …