发布时间:2021-03-08 浏览次数:3405

魏益民  教授   博士生导师


复旦大学数学科学学院   教授

复旦大学智能复杂体系基础理论与关键技术实验室   双聘教授




简介

担任国际学术期刊Computational and Applied Mathematics, Journal of Applied Mathematics and Computing,FILOMAT, 和 Communications in Mathematical Research,《高校计算数学学报》的编委. 在国际学术期刊Math. Comput., SIAM J. Sci. Comput.,SIAM J. Numer Anal., SIAM J. Matrix Anal. Appl., J. Sci. Comput., IEEE Trans. Auto. Control, IEEE Trans.Neural Network Learn. System, Neurocomputing 和 Neural Computation 等发表论文150余篇; 在EDP Science, Elsevier, Springer, World Scientific和科学出版社等出版英语专著5本. 5次入选爱思唯尔“中国高被引学者”榜单. Google学术引用8900余次,H 指数 48.

主要研究方向

数值线性代数,多重线性代数的快速算法及其应用

近期成果

【1】W.Ding and Y.Wei. Theory and Computation of Tensors: Multi- Dimensional Arrays, Elsevier, 2016.

【2】M.Che and Y.Wei. Randomized algorithms for the approximations of Tucker and the tensor train decompositions, Advances in Computational Mathematics, 45 (2019)395-428.

【3】X. Wang, M. Che, and Y. Wei. Neural networks based approach solving multi-linear systems with M-tensors, Neurocomputing, 351 (2019) 33-42.

【4】M.Che and Y.Wei. Theory and Computation of Complex Tensors and its Applications, Springer, Singapore, 2020.

【5】M. Che, Y. Wei, and H.Yan. The computation of low multilinear rank approximations of tensors via power scheme and random projection, SIAM Journal on Matrix Analysis and Applications, 41 (2020) 605-636.


发布时间:2021-03-08 浏览次数:3405

魏益民  教授   博士生导师


复旦大学数学科学学院   教授

复旦大学智能复杂体系基础理论与关键技术实验室   双聘教授




简介

担任国际学术期刊Computational and Applied Mathematics, Journal of Applied Mathematics and Computing,FILOMAT, 和 Communications in Mathematical Research,《高校计算数学学报》的编委. 在国际学术期刊Math. Comput., SIAM J. Sci. Comput.,SIAM J. Numer Anal., SIAM J. Matrix Anal. Appl., J. Sci. Comput., IEEE Trans. Auto. Control, IEEE Trans.Neural Network Learn. System, Neurocomputing 和 Neural Computation 等发表论文150余篇; 在EDP Science, Elsevier, Springer, World Scientific和科学出版社等出版英语专著5本. 5次入选爱思唯尔“中国高被引学者”榜单. Google学术引用8900余次,H 指数 48.

主要研究方向

数值线性代数,多重线性代数的快速算法及其应用

近期成果

【1】W.Ding and Y.Wei. Theory and Computation of Tensors: Multi- Dimensional Arrays, Elsevier, 2016.

【2】M.Che and Y.Wei. Randomized algorithms for the approximations of Tucker and the tensor train decompositions, Advances in Computational Mathematics, 45 (2019)395-428.

【3】X. Wang, M. Che, and Y. Wei. Neural networks based approach solving multi-linear systems with M-tensors, Neurocomputing, 351 (2019) 33-42.

【4】M.Che and Y.Wei. Theory and Computation of Complex Tensors and its Applications, Springer, Singapore, 2020.

【5】M. Che, Y. Wei, and H.Yan. The computation of low multilinear rank approximations of tensors via power scheme and random projection, SIAM Journal on Matrix Analysis and Applications, 41 (2020) 605-636.