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» Structured Learning with Approximate Inference
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KDD
2010
ACM
188views Data Mining» more  KDD 2010»
14 years 11 months ago
Inferring networks of diffusion and influence
Information diffusion and virus propagation are fundamental processes talking place in networks. While it is often possible to directly observe when nodes become infected, observi...
Manuel Gomez-Rodriguez, Jure Leskovec, Andreas Kra...
IJAR
2008
118views more  IJAR 2008»
14 years 9 months ago
Dynamic multiagent probabilistic inference
Cooperative multiagent probabilistic inference can be applied in areas such as building surveillance and complex system diagnosis to reason about the states of the distributed unc...
Xiangdong An, Yang Xiang, Nick Cercone
JMLR
2010
105views more  JMLR 2010»
14 years 4 months ago
Collective Inference for Extraction MRFs Coupled with Symmetric Clique Potentials
Many structured information extraction tasks employ collective graphical models that capture interinstance associativity by coupling them with various clique potentials. We propos...
Rahul Gupta, Sunita Sarawagi, Ajit A. Diwan
BMCBI
2007
197views more  BMCBI 2007»
14 years 9 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
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...