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» Graphical Models: Statistical inference vs. determination
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BIRD
2008
Springer
141views Bioinformatics» more  BIRD 2008»
13 years 9 months ago
Nested q-Partial Graphs for Genetic Network Inference from "Small n, Large p" Microarray Data
Abstract. Gaussian graphical models are widely used to tackle the important and challenging problem of inferring genetic regulatory networks from expression data. These models have...
Kevin Kontos, Gianluca Bontempi
CVPR
2000
IEEE
14 years 9 months ago
Order Parameters for Minimax Entropy Distributions: When Does High Level Knowledge Help?
Many problems in vision can be formulated as Bayesian inference. It is important to determine the accuracy of these inferences and how they depend on the problem domain. In recent...
Alan L. Yuille, James M. Coughlan, Song Chun Zhu, ...
CVPR
2008
IEEE
14 years 1 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
MOBICOM
2010
ACM
13 years 7 months ago
Inferring and mitigating a link's hindering transmissions in managed 802.11 wireless networks
In 802.11 managed wireless networks, the manager can address under-served links by rate-limiting the conflicting nodes. In order to determine to what extent each conflicting node ...
Eugenio Magistretti, Omer Gurewitz, Edward W. Knig...
BMCBI
2007
197views more  BMCBI 2007»
13 years 7 months ago
Boolean networks using the chi-square test for inferring large-scale gene regulatory networks
Background: Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that...
Haseong Kim, Jae K. Lee, Taesung Park