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Probabilistic Inductive Logic Programming

Bibliographic Details
Other Authors: De Raedt, Luc (Editor), Frasconi, Paolo (Editor), Kersting, Kristian (Editor), Muggleton, Stephen H. (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2008, 2008
Edition:1st ed. 2008
Series:Lecture Notes in Artificial Intelligence
Subjects:
Bioinformatics
Programming Techniques
Computational And Systems Biology
Computer Programming
Artificial Intelligence
Algorithms
Formal Languages And Automata Theory
Data Mining
Machine Theory
Data Mining And Knowledge Discovery
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • 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

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