Numerical method for the generalized nonnegative tensor factorization problem

In this paper, we consider the generalized nonnegative tensor factorization (GNTF) problem, which arises in multiple-tissue gene expression and multi-target tracking. Based on the Karhsh-Kuhn-Tucker conditions, the necessary condition of the local solution for the GNTF problem is given. The proximal alternating nonnegative least squares method is designed to solve it, and its convergence theorem is also derived. Numerical examples show that the new method is feasible and effective.

Automated summary

This paper considers the generalized nonnegative tensor factorization (GNTF) problem and proposes a proximal alternating nonnegative least squares method to solve it, along with proving its convergence theorem. Numerical examples demonstrate the feasibility and effectiveness of the new method.