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Probabilistic Inductive Logic Programming : Theory and Applications / edited by Luc Raedt, Paolo Frasconi, Kristian Kersting, Stephen Muggleton

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Lecture notes in computer science ; 4911Publisher: Berlin [u.a.] : Springer, 2008Description: Online-Ressource (VIII, 339 S.)ISBN:
  • 9783540786528
Subject(s): Genre/Form: Additional physical formats: 3540786511 | 9783540786511 | Buchausg. u.d.T.: Probabilistic inductive logic programming. Berlin : Springer, 2008. VIII, 339 S.DDC classification:
  • 006.31
  • 006.3
  • 004
MSC: MSC: *68-06 | 68N17 | 68T05 | 00B15LOC classification:
  • QA76.63
  • Q334-342 TJ210.2-211.495
DOI: DOI: 10.1007/978-3-540-78652-8Online resources: Summary: Probabilistic Inductive Logic Programming -- Formalisms and Systems -- Relational Sequence Learning -- Learning with Kernels and Logical Representations -- Markov Logic -- New Advances in Logic-Based Probabilistic Modeling by PRISM -- CLP( ): Constraint Logic Programming for Probabilistic Knowledge -- Basic Principles of Learning Bayesian Logic Programs -- The Independent Choice Logic and Beyond -- Applications -- Protein Fold Discovery Using Stochastic Logic Programs -- Probabilistic Logic Learning from Haplotype Data -- Model Revision from Temporal Logic Properties in Computational Systems Biology -- Theory -- A Behavioral Comparison of Some Probabilistic Logic Models -- Model-Theoretic Expressivity Analysis.PPN: PPN: 1646515587Package identifier: Produktsigel: ZDB-2-LNC | ZDB-2-SCS | ZDB-2-SXCS | ZDB-2-SEB
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Reproduktion, 2008 |2008||||||||||

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