Probabilistic Inductive Logic Programming [electronic resource] : Theory and Applications / edited by Luc Raedt, Paolo Frasconi, Kristian Kersting, Stephen Muggleton.
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- text
- computer
- online resource
- 9783540786528
- Computer science
- Computer software
- Data mining
- Artificial intelligence
- Bioinformatics
- Computer Science
- Artificial Intelligence (incl. Robotics)
- Programming Techniques
- Mathematical Logic and Formal Languages
- Algorithm Analysis and Problem Complexity
- Data Mining and Knowledge Discovery
- Computational Biology/Bioinformatics
- 006.3 23
- Q334-342
- TJ210.2-211.495
Item type | Current library | Call number | Status | Date due | Barcode | |
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Central Library | Available | E-45015 |
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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