ECE Seminar with Dr. John Wright

  • Starts: 4:00 pm on Wednesday, January 19, 2011

Robust Analysis of High-Dimensional Data

Dr. John Wright, Microsoft Research

Faculty Host: W. Clem Karl

Refreshments will be served outside Room 339 at 3:45 p.m.

Abstract: In this talk, Dr. Wright will introduce several recent theoretical and algorithmic advances in robust recovery of low-dimensional structure from high-dimensional data. He’ll show how to correctly and efficiently recover two important, closely-related types of low-dimensional structure: sparse vectors and low-rank matrices.

For sparse vectors, he will prove that as long as the signal of interest has a sufficiently sparse representation in a coherent dictionary, convex programming corrects large fractions of errors. In the same spirit, he will prove that convex programming recovers low-rank matrices from large fractions of errors and missing observations. He motivates these general problems from the perspective of automatic face recognition in computer vision and demonstrates how theoretical advances have inspired progress on this challenging problem.

He will discuss several additional applications of these tools including robust batch image alignment and registration, 3D shape recovery from multiple images, video stabilization and enhancement, web data analysis, indexing and search.

About the Speaker: John Wright received his Ph.D. in electrical engineering from the University of Illinois at Urbana-Champaign in October 2009. He is currently a researcher in the Visual Computing Group at Microsoft Research Asia. His research focuses on developing provably correct and efficient tools for recovering low-dimensional structure in high-dimensional datasets, even when data are missing or grossly corrupted. These techniques address critical estimation problems in imaging and vision applications such as automatic face recognition, video stabilization and tracking, image and data segmentation, and more. They’re also used in applications outside of vision – for example, in web data analysis and bioinformatics. His work has received a number of awards and honors, including the 2009 Lemelson-Illinois Prize for Innovation for his work on robust face recognition, the 2009 UIUC Martin Award for Excellence in Graduate Research, a 2008-2010 Microsoft Research Fellowship, a Carver Fellowship, and a UIUC Bronze Tablet award.

Photonics Center, 8 Saint Mary’s St., Room 339

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