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CSDA
2007
108views more  CSDA 2007»
15 years 22 days ago
Nonlinear random effects mixture models: Maximum likelihood estimation via the EM algorithm
Nonlinear random effects models with finite mixture structures are used to identify polymorphism in pharmacokinetic/ pharmacodynamic (PK/PD) phenotypes. An EM algorithm for maxim...
Xiaoning Wang, Alan Schumitzky, David Z. D'Argenio
INFOCOM
2009
IEEE
15 years 7 months ago
Robust Event Boundary Detection in Sensor Networks - A Mixture Model Based Approach
—Detecting event frontline or boundary sensors in a complex sensor network environment is one of the critical problems for sensor network applications. In this paper, we propose ...
Min Ding, Xiuzhen Cheng
WSC
2004
15 years 2 months ago
Global Likelihood Optimization Via the Cross-Entropy Method, with an Application to Mixture Models
Global likelihood maximization is an important aspect of many statistical analyses. Often the likelihood function is highly multi-extremal. This presents a significant challenge t...
Zdravko I. Botev, Dirk P. Kroese
116
Voted
ICIP
2006
IEEE
16 years 2 months ago
Video Event Detection using ICA Mixture Hidden Markov Models
In this paper, a framework that combines feature extraction, model learning, and likelihood computation, is presented for video event detection. First, the independent component a...
Jian Zhou, Xiao-Ping Zhang
95
Voted
ICML
2003
IEEE
16 years 1 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...