计算机工程与应用2017，Vol.53Issue(5)：181-186,6.DOI:10.3778/j.issn.1002-8331.1507-0091
非负矩阵分解的非单调自适应BB步长算法
Non-monotone adaptive Barzilai-Borwein step-size method for nonnegative matrix factorization
摘要
Abstract
Based on the Alternating Nonnegative Least Squares(ANLS) framework, an algorithm called Non-monotone Adaptive Barzilai-Borwein step-size (NABB) algorithm for nonnegative matrix factorization is proposed. The step-size of the algorithm satisfies the non-monotone line search though it is not obtained through line search, which ensures the global convergence of the algorithm. Furthermore, adaptive BB step-size and the gradient of the Lipschitz constant are also used to accelerate the rate of the convergence in this algorithm as usual. Finally, the algorithm is theoretically proved to be convergent. At the same time, the test results of numerical experiments and face recognition show that the proposed algo-rithm is effective and outruns other algorithms.关键词
非单调线搜索/自适应BB步长/非负矩阵分解Key words
non-monotone line search/adaptive Barzilai-Borweinstep-size/nonnegative matrix factorization分类
数理科学引用本文复制引用
王静,杨善学..非负矩阵分解的非单调自适应BB步长算法[J].计算机工程与应用,2017,53(5):181-186,6.基金项目
国家自然科学基金(No.61179040). （No.61179040）
