报告名称：Practical algorithms for tensor ring decomposition

主讲人：李寒宇 教授

邀请人：莫长鑫 讲师

时间：2022年12月30日   14:30

地点：腾讯会议（414 886 708）

主办单位：十大网投正规信誉官网

报告摘要：

Based on sketching techniques, we first propose two randomized algorithms for tensor ring (TR) decomposition. Specifically, on the basis of defining new tensor products and investigating their properties, the two algorithms are devised by applying the Kronecker sub-sampled randomized Fourier transform and TensorSketch to the alternative least squares (ALS) subproblems from TR decomposition. Considering that, in all the existing algorithms and our new randomized algorithms, the ALS subproblems have to be solved directly eventually, which may suffer from the intermediate data explosion issue, we then propose two strategies to tackle the computation of the subproblems. The first one is used to simplify the calculation of the coefficient matrices of the normal equations for the ALS subproblems, and the other one is to stabilize the ALS subproblems by QR factorizations on TR-cores. They can take full advantage of the structure of the coefficient matrices of the subproblems. Three corresponding algorithms are devised. Extensive numerical experiments on synthetic and real data are presented to test our methods.

 

专家简介：

李寒宇，博士、重庆大学教授、博士生导师。主要从事随机数值代数、统计计算、张量回归等方面的研究。先后主持国家自然科学基金项目、重庆市自然科学基金项目多项，在国际知名杂志发表学术论文多篇。