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» Parametric Structure of Probabilities in Bayesian Networks
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NECO
2008
108views more  NECO 2008»
13 years 7 months ago
Optimal Approximation of Signal Priors
In signal restoration by Bayesian inference, one typically uses a parametric model of the prior distribution of the signal. Here, we consider how the parameters of a prior model s...
Aapo Hyvärinen
AAAI
2007
13 years 10 months ago
Probabilistic Community Discovery Using Hierarchical Latent Gaussian Mixture Model
Complex networks exist in a wide array of diverse domains, ranging from biology, sociology, and computer science. These real-world networks, while disparate in nature, often compr...
Haizheng Zhang, C. Lee Giles, Henry C. Foley, John...
CVPR
2009
IEEE
14 years 2 months ago
Learning multi-modal densities on Discriminative Temporal Interaction Manifold for group activity recognition
While video-based activity analysis and recognition has received much attention, existing body of work mostly deals with single object/person case. Coordinated multi-object activi...
Ruonan Li, Rama Chellappa, Shaohua Kevin Zhou
BMCBI
2010
174views more  BMCBI 2010»
13 years 7 months ago
The effect of prior assumptions over the weights in BayesPI with application to study protein-DNA interactions from ChIP-based h
Background: To further understand the implementation of hyperparameters re-estimation technique in Bayesian hierarchical model, we added two more prior assumptions over the weight...
Junbai Wang
INFOCOM
2005
IEEE
14 years 1 months ago
BARD: Bayesian-assisted resource discovery in sensor networks
Data dissemination in sensor networks requires four components: resource discovery, route establishment, packet forwarding, and route maintenance. Resource discovery can be the mos...
Fred Stann, John S. Heidemann