| Subspace Learning for Sequential Data |
| Published date：2014-03-27 Provided by： |
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Title: Subspace Learning for Sequential Data
Guest Speaker：Professor Junbin Gao, Science in the School of Computing and Mathematics at Charles Sturt University
Time：2013-12-23, 10:00-12:00
Location：Meeting Room 7215, School of Science
Content &Introduction：
In this talk, I will present one of our recent research works on the Ordered Subspace Clustering (OSC) to segment data drawn from a sequentially ordered union of subspaces. Current subspace clustering techniques learn the relationships within a set of data and then use a separate clustering algorithm such as NCut for final segmentation. In contrast, our technique, under certain conditions, is capable of segmenting clusters intrinsically without providing the number of clusters as a parameter. Similar to Sparse Subspace Clustering (SSC) and Low-Rank Representation (LRR), we formulate the problem as one of finding a sparse representation but include a new penalty term to take care of sequential data. In the meantime I will talk about the deep link with the popular Dictionary Learning. Junbin Gao is a Professor in Computing Science in the School of Computing and Mathematics at Charles Sturt University, Australia, and also the Deputy Director of Centre for Research in Complex Systems. He graduated from Huazhong University of Science and Technology (HUST), China in 1982 with B.Sc. degree in Computational Mathematics and obtained PhD in computional mathematics from Dalian University of Technology, China in 1991. He was a senior lecturer, a lecturer in Computer Science from 2001 to 2005 at University of New England, Australia. Between 1999 and 2001 he worked as a senior research fellow in University of Southampton, England. 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, data mining, Bayesian learning and inference, and image analysis. In recent years he has won about $2M research grants from Australian Research Council (ARC) and industrial partners. |