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117
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ICML
2005
IEEE
16 years 3 months ago
Learning the structure of Markov logic networks
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
Stanley Kok, Pedro Domingos
104
Voted
CORR
2010
Springer
102views Education» more  CORR 2010»
15 years 2 months ago
Detecting Weak but Hierarchically-Structured Patterns in Networks
The ability to detect weak distributed activation patterns in networks is critical to several applications, such as identifying the onset of anomalous activity or incipient conges...
Aarti Singh, Robert D. Nowak, A. Robert Calderbank
125
Voted
IJAR
2007
130views more  IJAR 2007»
15 years 2 months ago
Bayesian network learning algorithms using structural restrictions
The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domai...
Luis M. de Campos, Javier Gomez Castellano
155
Voted
CORR
2008
Springer
126views Education» more  CORR 2008»
15 years 2 months ago
Mining User Profiles to Support Structure and Explanation in Open Social Networking
The proliferation of media sharing and social networking websites has brought with it vast collections of site-specific user generated content. The result is a Social Networking Di...
Avare Stewart, Ernesto Diaz-Aviles, Wolfgang Nejdl
100
Voted
MOBICOM
2004
ACM
15 years 8 months ago
A structured group mobility model for the simulation of mobile ad hoc networks
Realistic models for node movement are essential in simulating mobile ad hoc networks. Many MANET scenarios are most realistically represented using group movement, but existing g...
Ken Blakely, Bruce Lowekamp