报告人:喻高航 (杭州电子科技大学)

时  间: 2018年7月6日  15:30—16:30

地  点: 理科楼 LA106

摘  要: In this presentation, we would like to investigate some topics on "Tensor Optimization and Computations with Applications in Imaging Sciences".  Firstly, an adaptive gradient (AG) method is presented for generalized tensor eigenpairs. Global convergence and linear convergence rate could be established under some suitable conditions. Numerical results are reported to illustrate the efficiency of the proposed AG method. Comparing with the GEAP method, an adaptive shifted power method proposed by Tamara G. Kolda and Jackson R. Mayo [SIAM J. Matrix Anal. Appl., 35 (2014), pp. 1563-1581], the AG method is much faster and could reach the largest eigenpair with a higher probability. Secondly, we would like to show some high order tensor models with application to characterize non-Gaussian diffusion processes in diffusion tensor imaging (DTI).

报告人简介:喻高航，博士，教授，教育部新世纪优秀人才支持计划人选，剑桥大学应用数学与理论物理系留学归国人员。主要从事张量数据分析、大规模优化计算及其在机器学习、图像处理、医学影像中的应用研究。先后在SIAM Journal on Imaging Sciences, International Journal of Robust and Nonlinear Control，IEEE Signal Processing Letters，Journal of Mathematical Imaging and Vision，Inverse Problems, Neurocomputing, Computational Optimization and Applications, Journal of Optimization Theory and Applications, Optimization methods and software等国际期刊上发表30余篇SCI论文，主持4项国家自科基金、1项教育部博士点基金和1项教育部新世纪优秀人才支持计划项目等，有多篇论文入选ESI高被引榜单。自2013年起任国际学术期刊Statistics, Optimization and Information Computing 执行编委（Coordinating Editor）。现任国家自然科学基金项目通讯评审专家及多个国际SCI学术刊物的审稿人。

公司联系人: 李寒宇

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