Accurate Max-margin Training for Structured Output Spaces

Speaker:	Dr. Sunita SARAWAGI
		Department of Computer Science and Engineering
		Indian Institute of Technology
		Bombay

Title:		"Accurate Max-margin Training for Structured
		 Output Spaces"

Date:		Tuesday, 27 May 2008

Time:		10:30am - 11:30am

Venue:		Lecture Theatre H
		(Chen Kuan Cheng Forum, near lift nos. 27/28)
		HKUST

Abstract:

In this talk, I will present new insights and objectives for max-margin
training of structured models.  There are two popular formulations for
maximum margin training of structured spaces: margin scaling and slack
scaling. While margin scaling has been extensively used since it requires
the same kind of MAP inference as normal structured prediction, slack
scaling is believed to be more accurate and better-behaved.  I will
describe an efficient variational approximation to the slack scaling
method that solves its inference bottleneck while retaining its accuracy
advantage over margin scaling. Further I argue that existing scaling
approaches do not separate the true labeling comprehensively while
generating violating constraints. I will propose a new max-margin trainer
PosLearn that generates violators to ensure separation at each position of
a decomposable loss function.

******************
Biography:

Sunita Sarawagi researches in the fields of databases, data mining,
machine learning and statistics.  Her current research interests are
information integration, graphical models, probabilistic databases, and
domain adaptation.  She is associate professor at IIT Bombay. Prior to
that she was a research staff member at IBM Almaden Research Center. She
got her PhD in databases from the University of California at Berkeley and
a bachelor's degree from IIT Kharagpur.  She has several publications in
databases and data mining including a best paper award at the 1998 ACM
SIGMOD conference and several patents. She is on the editorial board of
the ACM TODS and ACM TKDD journals and ex-editor-in-chief of the ACM
SIGKDD newsletter.  She is program chair for the ACM SIGKDD 2008
conference and has served as program committee member for SIGMOD, VLDB,
SIGKDD, ICDE, and ICML conferences.