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GRASP Seminar Series: Fall 2007
November 16, 11:00 a.m., Wu & Chen Auditorium, Levine Hall (3330 Walnut Street)
Ben Taskar
University
of Pennsylvania
"Learning to Align"
Abstract: Problems
of alignment or correspondence of sequences, trees and other structured
objects of different types are predominant in many fields. Examples include
word alignment for machine translation, functional pathway correspondence
across species, matching of images/video and text. In these tasks, the
similarity between the corresponding elements is difficult to specify
and tune by hand, since it involves elements of different types: words
of different languages, proteins that are not sequence-homologous, image
regions and words. I will describe novel approaches to supervised
and weakly supervised learning of alignment models from data using tools
from convex optimization and probabilistic modeling.
Biography: Ben Taskar is Assistant Professor of Computer
and Information Science at the University of Pennsylvania. He
received his Ph.D. from Stanford University in 2004. His primary research
interests include machine learning and applications to computational
linguistics, computer vision, and computational biology.
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Last update:13 November, 2007