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【学术报告】An Efficient Algorithm for Computing the Approximate t-URV and its Applications
发布日期:2023-04-10    点击:

学术报告


 

报告题目: An Efficient Algorithm for Computing the Approximate t-URV and its Applications


时间:2023年4月13日星期四  16:00-17:30


报告人: 魏益民复旦大学)


报告地点:沙河主楼E404


腾讯会议531-118-801

 

报告摘要: This talk is devoted to the definition and computation of the tensor complete orthgonal decomposition of a third-order tensor called t-URV decompositions. We first give the definition for the t-URV decomposition of a third-order tensor and derive a deterministic algorithm for computing the t-URV. We then present a randomized algorithm to approximate t-URV, named compressed randomized t-URV (cort-URV). Note that t-URV and cort-URV are extensions of URV and compressed randomized URV from the matrix case to the tensor case, respectively. We also establish the deterministic and average-case error bounds for this algorithm. Finally, we illustrate the effectiveness of the proposed algorithm via several numerical examples, and we apply cort-URV to compress the data tensors from some image and video databases.

 

报告人简介:

魏益民,复旦大学数学学院教授,现担任国际学术期刊Computational and Applied Mathematics, Journal of Applied Mathematics and Computing, FILOMAT, 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 Neural Computation 等发表论文150余篇EDP Science, Elsevier, Springer, World Scientific和科学出版社等出版英语专著56次入选爱思唯尔中国高被引学者榜单Google学术引用9000余次,H指数48他的主要研究方向是数值线性代数,多重线性代数的快速算法及其应用。

 

 

邀请人:崔春风

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