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
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