Professor Ziyan Luo, Beijing Jiaotong University

Tensor-based modeling and computation emerge prominently with urgent demands from practical applications in the big data era. With the intrinsic sparsity in real data sets and the dimensionality reduction demands from applications, sparse tensor optimization (STO) is emerging, and efforts are distributed in a variety of specific applications, such as tensor regression in statistics, tensor recovery in imaging/video processing, and related engineering problems in data analysis. In this talk, we will give a brief introduction to the optimization models and algorithms of STO arising from several recent application works of our research group, including the traffic flow prediction, internet traffic anomaly detection, and background subtraction in video surveillance. Indeed, STO is heavily relied on the traditional sparse optimization and low-rank matrix optimization, and the optimization theory and algorithms for STO are still in the early stage. Researchers from Science and Engineering will be so welcomed to join in the study of STO.