报 告 人： 赵启斌，日本理化研究所革新智能综合研究中心

报告时间：11月17日（周二）10:00-12:00

报告地点：腾讯会议  会议 ID：219 853 884

邀 请 人：韩越兴 副教授

报告摘要：

In recent years, tensor networks (TNs) have been increasingly applied to machine learning and deep neural networks (DNN). This talk will present an overview of recent progress of TNs technology in machine learning from several aspects including TN for data decomposition, model parameter representation and function representation. Our team conducts research on this topic towards one question whether TNs are possibly developed to be a powerful ML model with new perspectives.

报告人简介:

Qibin Zhao received the Ph.D. degree in computer science from Shanghai Jiao Tong University, China in 2009. He is currently a team leader for tensor learning team at RIKEN Center for Advanced Intelligence Project, and is also a visiting professor in Saitama Institute of Technology, and a visiting associate professor in Tokyo University of Agriculture and Technology, Japan. His research interests include machine learning, tensor factorization and tensor networks, computer vision and brain signal processing. He has published more than 120 scientific papers in international journals and conferences and two monographs. He serves as an editorial board member for journal “Science China: Technological Sciences”, and area chair for the international conference of NeurIPS‘20, ICLR’21, AISTATS‘21, IJCAI’21 and ACML’20.