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ICPR
2004
IEEE
14 years 6 months ago
A Variational Approach for Color Image Segmentation
In this paper we use a variational Bayesian framework for color image segmentation. Each image is represented in the L*u*v color coordinate system before being segmented by the va...
Nikolaos Nasios, Adrian G. Bors
IJAR
2010
97views more  IJAR 2010»
13 years 4 months ago
Parameter estimation and model selection for mixtures of truncated exponentials
Bayesian networks with mixtures of truncated exponentials (MTEs) support efficient inference algorithms and provide a flexible way of modeling hybrid domains (domains containing ...
Helge Langseth, Thomas D. Nielsen, Rafael Rum&iacu...
TIT
2008
95views more  TIT 2008»
13 years 5 months ago
Distributed Estimation Via Random Access
The problem of distributed Bayesian estimation is considered in the context of a wireless sensor network. The Bayesian estimation performance is analyzed in terms of the expected F...
Animashree Anandkumar, Lang Tong, Ananthram Swami
NN
1997
Springer
174views Neural Networks» more  NN 1997»
13 years 9 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
NN
2006
Springer
127views Neural Networks» more  NN 2006»
13 years 5 months ago
The asymptotic equipartition property in reinforcement learning and its relation to return maximization
We discuss an important property called the asymptotic equipartition property on empirical sequences in reinforcement learning. This states that the typical set of empirical seque...
Kazunori Iwata, Kazushi Ikeda, Hideaki Sakai