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BMCBI
2008
98views more  BMCBI 2008»
13 years 9 months ago
GBNet: Deciphering regulatory rules in the co-regulated genes using a Gibbs sampler enhanced Bayesian network approach
Background: Combinatorial regulation of transcription factors (TFs) is important in determining the complex gene expression patterns particularly in higher organisms. Deciphering ...
Li Shen, Jie Liu, Wei Wang
ICML
2000
IEEE
14 years 9 months ago
Learning Bayesian Networks for Diverse and Varying numbers of Evidence Sets
We introduce an expandable Bayesian network (EBN) to handle the combination of diverse multiple homogeneous evidence sets. An EBN is an augmented Bayesian network which instantiat...
Zu Whan Kim, Ramakant Nevatia
ICDM
2010
IEEE
187views Data Mining» more  ICDM 2010»
13 years 6 months ago
Financial Forecasting with Gompertz Multiple Kernel Learning
Financial forecasting is the basis for budgeting activities and estimating future financing needs. Applying machine learning and data mining models to financial forecasting is both...
Han Qin, Dejing Dou, Yue Fang
FECS
2006
152views Education» more  FECS 2006»
13 years 10 months ago
Lessons Learned From Different Types of Projects in Software Engineering
Educators teaching software engineering face a large problem when trying to assign "real world" projects. Should the instructors make up "real world" projects ...
Jennifer A. Polack-Wahl
JCNS
2006
64views more  JCNS 2006»
13 years 8 months ago
A neuronal network for the logic of Limax learning
We construct a neuronal network to model the logic of associative conditioning as revealed in experimental results using the terrestrial mollusk Limax maximus. We show, in particul...
Pranay Goel, Alan Gelperin