讲座人：Jiwen Lu (a research scientist at the Advanced Digital Sciences Center (ADSC), Singapore, a research center of the University of Illinois at Urbana-Champaign (UIUC) which is located at Singapore.)讲座时间：2013.4.24（周三）上午 10:00-11:00讲座地点：复旦大学张江校区计算机楼 405联系人：路红 honglu@fudan.edu.cnAbstract: Subspace Learning has been one important research topic in computer vision and pattern recognition, owing to its wide range of applications such as image classification, information retrieval, action recognition and biometrics. In recent years, a number of subspace learning methods have been proposed and some of them have achieved reasonably good performance in many applications. In this talk, I will first discuss some shortcomings of the existing subspace learning methods. Then, I will introduce three of our recently proposed subspace learning methods: cost-sensitive subspace learning, discriminative multi-manifold analysis, and neighborhood repulsed metric learning. Lastly, I will show some experimental results on two biometrics recognition applications such as face recognition and kinship verification to show the efficacy of our proposed subspace learning methods. Bio: Dr. Jiwen Lu is a research scientist at the Advanced Digital Sciences Center (ADSC), Singapore, a research center of the University of Illinois at Urbana-Champaign (UIUC) which is located at Singapore. He received the B.Eng. degree in mechanical engineering and the M.Eng. degree in electrical engineering from the Xi’an University of Technology, Xi'an, China, in 2003 and 2006, respectively, and the Ph.D. degree in electrical engineering from the Nanyang Technological University, Singapore, in 2011. His research interests include computer vision, pattern recognition, machine learning and biometrics. He has authored more than 70 scientific papers in peer-reviewed journals and conferences including some top venues such as IEEE TPAMI, TIP, TCSVT, TSMC-B, TIFS, ICCV, CVPR and ACM MM. He serves as a reviewer for more than 30 academic journals and conferences such as TPAMI, TIP, TNNLS, TCSVT, ICCV, CVPR and ECCV. He received the best student paper award finalist of ICME 2011, and the best student paper award from the Pattern Recognition and Machine Intelligence Society (PREMIA) of Singapore, in 2011 and 2012, respectively.
