A proximal ANLS algorithm for nonnegative tensor factorization with a periodic enhanced line search

作者：Bunker Douglas; Han Lixing; Zhang Shuhua^*

来源：Applications of Mathematics, 2013, 58(5): 493-509.

DOI：10.1007/s10492-013-0026-2

• nonnegative tensor factorization
• proximal method
• alternating least squares
• enhanced line search
• global convergence

The Alternating Nonnegative Least Squares (ANLS) method is commonly used for solving nonnegative tensor factorization problems. In this paper, we focus on algorithmic improvement of this method. We present a Proximal ANLS (PANLS) algorithm to enforce convergence. To speed up the PANLS method, we propose to combine it with a periodic enhanced line search strategy. The resulting algorithm, PANLS/PELS, converges to a critical point of the nonnegative tensor factorization problem under mild conditions. We also provide some numerical results comparing the ANLS and PANLS/PELS methods.

• 出版日期2013-10
• 单位天津大学