[Colloquium] Reminder: Talk today Jerry Zhu @ 3:00pm TTI-C

Katherine Cumming kcumming at tti-c.org
Mon Apr 18 08:45:51 CDT 2005


Speaker:  Jerry Zhu, Carnegie Mellon University
Speaker's Homepage:  http://www-2.cs.cmu.edu/~zhuxj/
 
Time:  Monday, April 18, 2005 @ 3:00pm
Place:  TTI-C Conference Room
 
Title:
Semi-Supervised Learning with Graphs
Abstract:
In traditional machine learning approaches to classification, one uses
only a labeled set to train the classifier. Labeled data however are
often difficult, expensive, or time consuming to obtain, as they require
the efforts of experienced human annotators. Meanwhile unlabeled data
may be relatively easy to collect, but there has been few ways to use
them. Semi-supervised learning addresses this problem by using large
amount of unlabeled data, together with the labeled data, to build
better classifiers. Because semi-supervised learning requires less human
effort and gives higher accuracy, it is of great interest both in theory
and in practice.

One can ask many questions: How to use unlabeled data? Is there a
probabilistic framework? What assumptions does it make, and how to meet
the assumptions? Can it work together with my favorite classifiers, e.g.
support vector machines? Will it work on sequential data? Can it handle
large problems? What if we have the freedom to choose which items to
label in the first place? Most importantly, does it work in practice? In
this talk I answer these questions. I present a series of novel
semi-supervised learning methods, and show unlabeled data improve
performance on text categorization, image recognition and other tasks.
The same technologies have great potential in many areas, including
speech recognition and bioinformatics. 
If you have questions, or would like to meet the speaker, please contact
Katherine at 4-1994 or kcumming at tti-c.org. For information on future
TTI-C talks or events, please go to the TTI-C Events
<http://ttic.uchicago.edu/events/events_dyn.php>  page. 
 
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