Massive multi- and high-dimensional data from vision research offer rich information, which can be used in solving real life challenging problems. In traditional machine learning paradigm, this type of structured data is processed by simply vectorising them without considering their intrinsic "spatial" correlation within the data. In this seminar, I will focus on reviewing some of my recent work on tensorial data analysis and clustering and try to give an introduction to the low rank representation on tensors, multidimensional dictionary learning and tensorial data clustering.
Professor Junbin Gao graduated from Huazhong University of Science and Technology (HUST), China in 1982 with B.Sc. degree in Computational Mathematics and obtained PhD from Dalian University of Technology, China in 1991. In July of 2005, he joined the School of Information Technology (now Computing and Mathematics) at Charles Sturt University, Australia, as an Associate Professor in Computing Science. He was a senior lecturer, a lecturer in Computer Science from 2001 to 2005 at University of New England, Australia. From 1982 to 2001 he was an associate lecturer, lecturer, associate professor and professor in Department of Mathematics at HUST. His main research interests include machine learning, kernel method, Bayesian learning and inference, and image processing. Professor Gao has published more than 220 papers and two books on machine learning, pattern recognition and Bayesian inference.