Computer Science

CS Colloquium Speaker: Dr. Jia Xu

When: November 16th, 2015 from 10-11am
Where: 1131 Kemper Hall
Title: Better bootstraps, better accuracy: in theory, in practice, in translation
Abstract: Bagging [Breiman, 96] and its variants is one of the most
popular methods in aggregating classifiers and regressors. Its original
analysis assumes that the bootstraps are built from an unlimited,
independent source of samples. In the real world this analysis fails
because there is a limited number of training samples. We analyze the
effect of intersections between bootstraps to train different base
predictors, which shows that the real-world bagging behaves very
differently than its ideal analog [Breiman, 96]. Most importantly, we
provide an alternative subsampling method called design-bagging based
on a new construction of combinatorial designs. We prove that this is
universally better than bagging.  Our analytical results are backed up
by experiments on general classification and regression settings, and
significantly improved all machine translation systems we used in the
NIST-15 C-E competition.Bio: Jia Xu is an associate professor at ICT/CAS, after being an
assistant professor in Tsinghua University and a senior researcher at
DFKI lecturing at Saarland University in Germany. She worked at IBM
Watson and MSR Redmond during her Ph.D. advised by Hermann Ney at
RWTH-Aachen University. Her current research interests are in Machine
Learning with a focus towards highly competitive machine translation
systems, where she led and participated in teams winning first place in
WMT-11, TC-Star -05-07 and NIST-08. In NIST-15 she led one more team
that won 4th place, which is the 1st among academic institutions.

1131 Kemper Hall

Loading Map....