E-Book, Englisch, 341 Seiten, eBook
De Raedt / Frasconi / Kersting Probabilistic Inductive Logic Programming
2008
ISBN: 978-3-540-78652-8
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 341 Seiten, eBook
Reihe: Lecture Notes in Artificial Intelligence
ISBN: 978-3-540-78652-8
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
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.
