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Handling Big Data: A Machine Learning Perspective

Speaker: Wei Liu
IBM Thomas J. Watson Research Center

November 26, 2013 - 4:00 p.m. to 5:00 p.m.
Location: CII (Low) 3051
Hosted By: Dr. Heng Ji (x2103)


With the rapid development of the Internet, nowadays tremendous amounts of data including images and videos, up to millions or billions, can be collected for training machine learning models. Inspired by this trend, my current work is dedicated to developing large-scale machine learning techniques for the purpose of making classification and nearest neighbor search practical on big data.My first approach is to explore data graphs to aid classification and nearest neighbor search. A graph offers an attractive way of representing data and discovering the essential information such as the neighborhood structure. However, both of the graph construction process and graph-based learning techniques become computationally prohibitive at a large scale. To this end, I propose an efficient large graph construction approach and subsequently apply it to develop scalable semi-supervised learning and unsupervised hashing algorithms. To address other practical application scenarios, I further develop advanced hashing techniques that incorporate supervised information or leverage unique formulations to cope with new forms of queries such as hyperplanes. All of the machine learning techniques I have proposed emphasize and pursue excellent performance in both speed and accuracy. The addressed problems, classification and nearest neighbor search, are fundamental for many practical problems across various disciplines. Therefore, I expect that the proposed solutions based on graphs and hashing will have a tremendous impact on a great number of realistic large-scale applications.


Wei Liu received the M.Phil. and Ph.D. degrees in electrical engineering from Columbia University, New York, NY, USA in 2012. Currently, he is a research staff member of IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA. He has been the Josef Raviv Memorial Postdoctoral Fellow at IBM Thomas J. Watson Research Center for one year since 2012. His research interests include machine learning, data mining, computer vision, and information retrieval. Dr. Liu is the recipient of the 2011-2012 Facebook Fellowship.

Last updated: November 12, 2013