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» Complexity of Inference in Graphical Models
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NIPS
2004
13 years 10 months ago
Exponential Family Harmoniums with an Application to Information Retrieval
Directed graphical models with one layer of observed random variables and one or more layers of hidden random variables have been the dominant modelling paradigm in many research ...
Max Welling, Michal Rosen-Zvi, Geoffrey E. Hinton
CGF
2010
182views more  CGF 2010»
13 years 7 months ago
A Data-driven Segmentation for the Shoulder Complex
The human shoulder complex is perhaps the most complicated joint in the human body being comprised of a set of three bones, muscles, tendons, and ligaments. Despite this anatomica...
Q. Youn Hong, Sang Il Park, Jessica K. Hodgins
CVPR
2008
IEEE
14 years 3 months ago
Bayesian tactile face
Computer users with visual impairment cannot access the rich graphical contents in print or digital media unless relying on visual-to-tactile conversion, which is done primarily b...
Zheshen Wang, Xinyu Xu, Baoxin Li
ICML
2005
IEEE
14 years 9 months ago
Variational Bayesian image modelling
We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models--Hidden Markov Random Fields (H...
Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang
ACCV
2006
Springer
14 years 3 months ago
Online Updating Appearance Generative Mixture Model for Meanshift Tracking
This paper proposes an appearance generative mixture model based on key frames for meanshift tracking. Meanshift tracking algorithm tracks object by maximizing the similarity betwe...
Jilin Tu, Hai Tao, Thomas S. Huang