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» Modeling Dependable Systems using Hybrid Bayesian Networks
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BIOCOMP
2008
13 years 10 months ago
Reverse Engineering Module Networks by PSO-RNN Hybrid Modeling
Background: Inferring a gene regulatory network (GRN) from high throughput biological data is often an under-determined problem and is a challenging task due to the following reas...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...
AIME
2009
Springer
14 years 3 months ago
Causal Probabilistic Modelling for Two-View Mammographic Analysis
Abstract. Mammographic analysis is a difficult task due to the complexity of image interpretation. This results in diagnostic uncertainty, thus provoking the need for assistance by...
Marina Velikova, Maurice Samulski, Peter J. F. Luc...
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 9 months ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
BDIM
2008
IEEE
205views Business» more  BDIM 2008»
14 years 3 months ago
Mining semantic relations using NetFlow
—Knowing the dependencies among computing assets and services provides insights into the computing and business landscape, therefore, facilitating low-risk timely changes in supp...
Alexandru Caracas, Andreas Kind, Dieter Gantenbein...
AAAI
1998
13 years 10 months ago
Bayesian Reasoning in an Abductive Mechanism for Argument Generation and Analysis
Our argumentation system, NAG, uses Bayesian networks in a user model and in a normative model to assemble and assess arguments which balance persuasiveness with normative correct...
Ingrid Zukerman, Richard McConachy, Kevin B. Korb