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» Weighted versus Probabilistic Logics
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ICML
2005
IEEE
14 years 5 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
CIKM
2005
Springer
13 years 10 months ago
Information retrieval and machine learning for probabilistic schema matching
Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain, or for distribute...
Henrik Nottelmann, Umberto Straccia
VTS
2002
IEEE
120views Hardware» more  VTS 2002»
13 years 9 months ago
Software-Based Weighted Random Testing for IP Cores in Bus-Based Programmable SoCs
We present a software-based weighted random pattern scheme for testing delay faults in IP cores of programmable SoCs. We describe a method for determining static and transition pr...
Madhu K. Iyer, Kwang-Ting Cheng
ECCV
2008
Springer
13 years 6 months ago
Event Modeling and Recognition Using Markov Logic Networks
Abstract. We address the problem of visual event recognition in surveillance where noise and missing observations are serious problems. Common sense domain knowledge is exploited t...
Son Dinh Tran, Larry S. Davis
ECSQARU
2007
Springer
13 years 10 months ago
Logical Compilation of Bayesian Networks with Discrete Variables
This paper presents a new approach to inference in Bayesian networks. The principal idea is to encode the network by logical sentences and to compile the resulting encoding into an...
Michael Wachter, Rolf Haenni