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» On Bayesian model and variable selection using MCMC
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AAAI
2007
15 years 4 days 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...
TSP
2011
90views more  TSP 2011»
14 years 4 months ago
Radar HRRP Statistical Recognition With Local Factor Analysis by Automatic Bayesian Ying-Yang Harmony Learning
—Radar high-resolution range profiles (HRRPs) are typical high-dimensional, non-Gaussian and interdimension dependently distributed data, the statistical modelling of which is a...
Lei Shi, Penghui Wang, Hongwei Liu, Lei Xu, Zheng ...
ISIPTA
1999
IEEE
108views Mathematics» more  ISIPTA 1999»
15 years 2 months ago
Coherent Models for Discrete Possibilistic Systems
We consider discrete possibilistic systems for which the available information is given by one-step transition possibilities and initial possibilities. These systems can be repres...
Hugo J. Janssen, Gert De Cooman, Etienne E. Kerre
BMCBI
2010
150views more  BMCBI 2010»
14 years 7 months ago
Kernel based methods for accelerated failure time model with ultra-high dimensional data
Background: Most genomic data have ultra-high dimensions with more than 10,000 genes (probes). Regularization methods with L1 and Lp penalty have been extensively studied in survi...
Zhenqiu Liu, Dechang Chen, Ming Tan, Feng Jiang, R...
WSC
1997
14 years 11 months ago
Selecting the Best System: A Decision-Theoretic Approach
The problem of selecting the best system from a finite set of alternatives is considered from a Bayesian decision-theoretic perspective. The framework presented is quite general,...
Stephen E. Chick