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» Modelling of Complex Supply Networks
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DAC
2008
ACM
14 years 11 months ago
DeMOR: decentralized model order reduction of linear networks with massive ports
Model order reduction is an efficient technique to reduce the system complexity while producing a good approximation of the input-output behavior. However, the efficiency of reduc...
Boyuan Yan, Lingfei Zhou, Sheldon X.-D. Tan, Jie C...
CEC
2010
IEEE
14 years 5 months ago
Parameter estimation with term-wise decomposition in biochemical network GMA models by hybrid regularized Least Squares-Particle
High-throughput analytical techniques such as nuclear magnetic resonance, protein kinase phosphorylation, and mass spectroscopic methods generate time dense profiles of metabolites...
Prospero C. Naval, Luis G. Sison, Eduardo R. Mendo...
BMCBI
2007
169views more  BMCBI 2007»
14 years 10 months ago
Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and i
Background: Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targ...
Abdallah Sayyed-Ahmad, Kagan Tuncay, Peter J. Orto...
UAI
1997
14 years 11 months ago
Exploring Parallelism in Learning Belief Networks
It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link lookahead search. When a multil...
Tongsheng Chu, Yang Xiang
ICML
2004
IEEE
15 years 10 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...