报告人：陶大程教授 

报告题目：MahNMF: Manhattan Non-negative Matrix Factorization 

报告时间：10月24日9：00-10：15 

主持人：刘青山院长 

报告简介： 

Non-negative matrix factorization (NMF) approximates a non-negative matrix X by the product of two non-negative low-rank factor matrices W and H. We introduce Manhattan NMF (MahNMF) to minimize the Manhattan distance between X and W^TH for modeling the heavy tailed Laplace noise. Similar to sparse and low-rank matrix decomposition models, such as robust principal component analysis and GoDec, MahNMF robustly estimates the low-rank part and the sparse part of a non-negative matrix and thus performs effectively when data are contaminated by outliers. MahNMF can be solved by two fast optimization algorithms: rank-one residual iteration and Nesterov's smoothing method, and is applicable to various practical problems by considering different constraints and regularizations, such as box-constraint, manifold regularization, and group sparsity. Experiments are conducted on both synthetic and real-world datasets, such as face images, natural scene images, surveillance videos and multi-view natural image datasets. 

报告人简介： 

Dacheng Tao is Professor of Computer Science with the Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology in the University of Technology, Sydney, and a visiting professor in Birkbeck - University of London, Shanghai Jiaotong University, Xidian University, Huazhong University of Science and Technology, and Wuhan University. 

Previously, he worked as a Nanyang endorsed academic staff in the Nanyang Technological University and an assistant professor in the Hong Kong Polytechnic University. He received his BEng degree from University of Science and Technology of China, his MPhil degree from the Chinese University of Hong Kong, and his PhD from the University of London. 

He mainly applies statistics and mathematics for data analysis problems in machine learning, data mining & engineering, computer vision, image processing, multimedia, video surveillance and neuroscience. He has authored and co-authored more than 200 scientific articles at top venues including IEEE T-PAMI, T-IP, T-SP, T-NNLS, T-KDE, CVPR, ECCV, AISTATS, ICDM; ACM Multimedia and KDD, with best paper awards, such as the best theory/algorithm paper runner up award in IEEE ICDM'07. 

His Erdös number is 3. He received a K.C. WONG Education Foundation Award from Chinese Academic of Sciences and a runner up award for the Outstanding Young Researcher in Image & Vision Computing. He was/is a guest editor of 10 special issues, an editor of 10 journals, including IEEE Trans. on Systems, Man and Cybernetics: Part B (T-SMCB), IEEE Trans. on Circuits and Systems for Video Technology (T-CSVT), IEEE Trans. on Knowledge and Data Engineering (T-KDE), Pattern Recognition (Elsevier), and Computational Statistics & Data Analysis (Elsevier). 

He has edited five books on several topics of optical pattern recognition and its applications. He has (co-) chaired for special sessions, invited sessions, workshops, panels and conferences for 30+ times. He has served for 100+ major conferences including VCIP, CVPR, ICCV, ECCV, IJCAI, NIPS, ICDM, SIGKDD and ACM Multimedia, and more than 50 prestigious international journals including T-PAMI, IJCV, T-IP, Artificial Intelligence, Machine Learning Journal and T-KDE. 

He is a senior member of the IEEE, an Elected Member of the International Statistical Institute (ISI), a Fellow of the International Association of Pattern Recognition (IAPR), a Fellow of the British Computer Society (BCS), and a Fellow of the IET/IEE. He is a chair of the IEEE SMCS Technical Committee (TC) on Cognitive Computing. 

信息与控制学院 

2012-10-23