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» A finiteness theorem for Markov bases of hierarchical models
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ICIP
2010
IEEE
13 years 5 months ago
Bayesian regularization of diffusion tensor images using hierarchical MCMC and loopy belief propagation
Based on the theory of Markov Random Fields, a Bayesian regularization model for diffusion tensor images (DTI) is proposed in this paper. The low-degree parameterization of diffus...
Siming Wei, Jing Hua, Jiajun Bu, Chun Chen, Yizhou...
ICRA
2006
IEEE
202views Robotics» more  ICRA 2006»
14 years 1 months ago
Primitive Communication based on Motion Recognition and Generation with Hierarchical Mimesis Model
— Communication skill is essential for social robots in various environments such as homes, offices, and hospitals, where the robots are expected to interact with humans. In thi...
Wataru Takano, Katsu Yamane, Tomomichi Sugihara, K...
ICIP
1995
IEEE
14 years 8 months ago
3D super-resolution using generalized sampling expansion
A 3D super-resolution algorithm is proposed below, based on a probabilistic interpretation of the ndimensional version of Papoulis' generalized sampling theorem. The algorith...
Hassan Shekarforoush, Marc Berthod, Josiane Zerubi...
ICML
2005
IEEE
14 years 8 months ago
Learning hierarchical multi-category text classification models
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
Craig Saunders, John Shawe-Taylor, Juho Rousu, S&a...
GECCO
2008
Springer
158views Optimization» more  GECCO 2008»
13 years 8 months ago
Convergence analysis of quantum-inspired genetic algorithms with the population of a single individual
In this paper, the Quantum-inspired Genetic Algorithms with the population of a single individual are formalized by a Markov chain model using a single and the stored best individ...
Mehrshad Khosraviani, Saadat Pour-Mozafari, Mohamm...