北航数学论坛学术报告
Tensor Representations in Data Science
Michael NG（Hong Kong Baptist University）
报告时间：2025年3月13日星期四 10：30-11：30
报告地点：沙河主楼E404
报告摘要: Higher-order tensors are suitable for representing multi-dimensional data in real-world, e.g., color images and videos, low-rank tensor representation has become one of the emerging areas in machine learning and computer vision. However, classical low-rank tensor representations can solely represent multi-dimensional discrete data on meshgrid, which hinders their potential applicability in many scenarios beyond meshgrid. In this talk, we discuss the recent development of tensor representations in data science. Both theoretical results and numerical examples are presented to demonstrate the usefulness of tensor representations.
报告人简介：Prof. Michael Ng is a Chair Professor of Mathematics and a Chair Professor of Data Science with Hong Kong Baptist University, Hong Kong. His research interests include bioinformatics, image processing, scientific computing, and data mining.
Dr. Ng serves as an editorial board member for several international journals. He is selected for the 2017 class of fellows of the Society for Industrial and Applied Mathematics. He received the Feng Kang Prize for his significant contributions in scientific computing.
邀请人：崔春风
