Probabilistic Inductive Logic Programming 2008

• Luc De Raedt, Kristian Kersting:
  Probabilistic Inductive Logic Programming. 1-27
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• Kristian Kersting, Luc De Raedt, Bernd Gutmann, Andreas Karwath, Niels Landwehr:
  Relational Sequence Learning. 28-55
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• Paolo Frasconi, Andrea Passerini:
  Learning with Kernels and Logical Representations. 56-91
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• Pedro Domingos, Stanley Kok, Daniel Lowd, Hoifung Poon, Matthew Richardson, Parag Singla:
  Markov Logic. 92-117
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• Taisuke Sato, Yoshitaka Kameya:
  New Advances in Logic-Based Probabilistic Modeling by PRISM. 118-155
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• Vítor Santos Costa, David Page, James Cussens:
  CLP(BN): Constraint Logic Programming for Probabilistic Knowledge. 156-188
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• Kristian Kersting, Luc De Raedt:
  Basic Principles of Learning Bayesian Logic Programs. 189-221
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• David Poole:
  The Independent Choice Logic and Beyond. 222-243
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• Jianzhong Chen, Lawrence A. Kelley, Stephen Muggleton, Michael J. E. Sternberg:
  Protein Fold Discovery Using Stochastic Logic Programs. 244-262
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• Niels Landwehr, Taneli Mielikäinen:
  Probabilistic Logic Learning from Haplotype Data. 263-286
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• François Fages, Sylvain Soliman:
  Model Revision from Temporal Logic Properties in Computational Systems Biology. 287-304
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• Stephen Muggleton, Jianzhong Chen:
  A Behavioral Comparison of Some Probabilistic Logic Models. 305-324
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• Manfred Jaeger:
  Model-Theoretic Expressivity Analysis. 325-339
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