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AIME
2007
Springer
16 years 4 days ago
Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine
Traditional Chinese medicine (TCM) is an important avenue for disease prevention and treatment for the Chinese people and is gaining popularity among others. However, many remain s...
Nevin Lianwen Zhang, Shihong Yuan, Tao Chen, Yi Wa...
NIPS
1998
15 years 7 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
JMLR
2010
134views more  JMLR 2010»
15 years 22 days ago
Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Jan Lemeire, Kris Steenhaut
AAAI
2008
15 years 8 months ago
Factored Models for Probabilistic Modal Logic
Modal logic represents knowledge that agents have about other agents' knowledge. Probabilistic modal logic further captures probabilistic beliefs about probabilistic beliefs....
Afsaneh Shirazi, Eyal Amir
IJAR
2010
97views more  IJAR 2010»
15 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...