The Generalized CEM Algorithm

The Generalized CEM Algorithm (1999)

Cached

Download Links

[www.media.mit.edu]

by Tony Jebara , Alex Pentland

Venue:	In Advances in Neural Information Processing Systems 12
Citations:	4 - 0 self

Versions

Version History

Metadata Version 3

User correction supplied by SystemCorrections

Datum	Value	Source
TITLE	The Generalized CEM Algorithm	SVM HeaderParse 0.1
AUTHOR NAME	Tony Jebara	SVM HeaderParse 0.1
AUTHOR AFFIL	MIT Media Lab	SVM HeaderParse 0.2
AUTHOR ADDR	20 Ames St.; Cambridge, MA 02139	SVM HeaderParse 0.1
AUTHOR NAME	Alex Pentland	SVM HeaderParse 0.1
AUTHOR AFFIL	MIT Media Lab	SVM HeaderParse 0.2
AUTHOR ADDR	20 Ames St.; Cambridge, MA 02139	SVM HeaderParse 0.1
ABSTRACT	We propose a general approach for estimating the parameters of latent variable probability models to maximize conditional likelihood and discriminant criteria. Unlike joint likelihood, these objectives are better suited for classification and regression. The approach utilizes and extends the previously introduced CEM framework (Conditional Expectation Maximization), which reformulates EM to handle the conditional likelihood case. We generalize the CEM algorithm to estimate any mixture of exponential family densities. This includes structured graphical models over exponential families, such as HMMs. The algorithm efficiently takes advantage of the factorization of the underlying graph. In addition, the new CEM bound is tighter and more rigorous than the original one. The final result is a CEM algorithm that mirrors the EM algorithm where both estimate a variational lower bound on their respective incomplete objective functions, and both generate the same standard M-steps ...	user correction - Legacy Corrections
YEAR	1999	INFERENCE
VENUE	In Advances in Neural Information Processing Systems 12	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
VOLUME	12	INFERENCE
CITATIONS	7 found	ParsCit 1.0