Sciweavers

49 search results - page 1 / 10
» Particle methods for maximum likelihood estimation in latent...
Sort
View
SAC
2008
ACM
13 years 4 months ago
Particle methods for maximum likelihood estimation in latent variable models
Standard methods for maximum likelihood parameter estimation in latent variable models rely on the Expectation-Maximization algorithm and its Monte Carlo variants. Our approach is ...
Adam M. Johansen, Arnaud Doucet, Manuel Davy
CSDA
2006
94views more  CSDA 2006»
13 years 4 months ago
Simulation-based approach to estimation of latent variable models
We propose a simulation-based method for calculating maximum likelihood estimators in latent variable models. The proposed method integrates a recently developed sampling strategy...
Zhiguang Qian, Alexander Shapiro
ECML
2005
Springer
13 years 10 months ago
U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models
Abstract. In this paper we consider latent variable models and introduce a new U-likelihood concept for estimating the distribution over hidden variables. One can derive an estimat...
JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin ...
CVPR
2007
IEEE
14 years 6 months ago
Kernel-based Tracking from a Probabilistic Viewpoint
In this paper, we present a probabilistic formulation of kernel-based tracking methods based upon maximum likelihood estimation. To this end, we view the coordinates for the pixel...
Quang Anh Nguyen, Antonio Robles-Kelly, Chunhua Sh...
ICML
2003
IEEE
14 years 5 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...