Sparse Subspace Clustering

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CIS Colloquium, Dec 05, 2012, 11:15AM – 12:15PM, Wachman 447

Sparse Subspace Clustering

Rene Vidal , Johns Hopkins University

In the era of data deluge, the development of methods for discovering structure in high-dimensional data is becoming increasingly important. Traditional approaches often assume that the data is sampled from a single low-dimensional manifold. However, in many applications in signal/image processing, machine learning and computer vision, data in multiple classes lie in multiple low-dimensional subspaces of a high-dimensional ambient space. In this talk, I will present methods from algebraic geometry, sparse representation theory and rank minimization for clustering and classification of data in multiple low-dimensional subspaces. I will show how these methods can be extended to handle noise, outliers as well as missing data. I will also present applications of these methods to video segmentation and face clustering.

Professor Rene Vidal received the BS degree in electrical engineering (highest honors) from the Pontificia Universidad Catolica de Chile in 1997 and the MS and PhD degrees in electrical engineering and computer sciences from the University of California, Berkeley, in 2000 and 2003, respectively. He was a research fellow at the National ICT Australia in the Fall of 2003 and currently is an associate professor in the Department of Biomedical Engineering at The Johns Hopkins University. He has coauthored more than 150 articles in biomedical image analysis, computer vision, machine learning, hybrid systems, and robotics. He is a recipient of the 2012 J.K. Aggarwal Prize “for outstanding contributions to generalized principal component analysis (GPCA) and subspace clustering in computer vision and pattern recognition,” the 2012 Best Paper Award in Medical Robotics and Computer Assisted Interventions, 2011 Best Paper Award Finalist at the IEEE Conference on Decision and Control, the 2009 ONR Young Investigator Award, the 2009 Sloan Research Fellowship, the 2005 NFS CAREER Award, and the 2004 Best Paper Award Honorable Mention at the European Conference on Computer Vision. He also received the 2004 Sakrison Memorial Prize for completing an exceptionally documented piece of research, the 2003 Eli Jury award for outstanding achievement in the area of systems, communications, control, or signal processing, the 2002 Student Continuation Award from NASA Ames, the 1998 Marcos Orrego Puelma Award from the Institute of Engineers of Chile, and the 1997 Award of the School of Engineering of the Pontificia Universidad Catolica de Chile to the best graduating student of the school. He is a senior member of the IEEE and the ACM.