报告人：赵熙乐教授

报告题目：The Transform-Based Tensor Modeling and Computing.

报告摘要：

(1) Recently, tensor modeling and computing play a fundamental role in the modern multi-dimensional data processing. In this talk, we will discuss how to tackle the challenges in tensor modeling and computing from the transform perspective. On one hand, we will review the evolution of the transform-based tensor nuclear norm, which captures the intrinsic global structure of multi-dimensional data. On the other hand, we will discuss how to design the fast algorithms from the transform perspective.

(2) The linear transform-based tensor nuclear norm methods have recently obtained promising results for tensor completion. The main idea of these methods is exploiting the low-rank structure of frontal slices of the targeted tensor under the linear transform along the third mode. In this talk, we will introduce a nonlinear transform-based TNN. More concretely, the proposed nonlinear transform is a composite transform consisting of the linear semi-orthogonal transform along the third mode and the element-wise nonlinear transform on frontal slices of the tensor under the linear semi-orthogonal transform. The two transforms in the composite transform are indispensable and complementary to fully exploit the underlying low-rankness.

报告时间：2022年10月29日上午8:00-11:00

报告形式：腾讯会议；会议号：129-153-030

获取会议密码请发邮件至：mathywj@hit.edu.cn

报告人简介：赵熙乐，电子科技大学教授、博士生导师。担任中国工业与应用数学学会副秘书长，入选电子科技大学百人计划和四川省学术和技术带头人后备人选。主要研究兴趣为图像处理和机器学习的数学理论和方法，撰写Elsevier出版社和科学出版社出版的学术专著章节2章， 在权威SIAM 系列期刊(SISC和SIIMS)和IEEE系列期刊(TIP、TNNLS、TCYB、TCI和TGRS)及计算机学会A类会议CVPR、AAAI和ACMMM等发表研究工作。主持国家自然科学基金面上项目和青年项目、四川省面上项目、华为技术有限公司技术开发项目等。研究成果获四川省科技进步一等奖两项(自然科学类、科技进步类)，中国计算数学学会青年优秀论文竞赛二等奖、第一、第二届连续两届川渝科技学术大会优秀论文一等奖等。