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Books Books 1 - 10 of about 21 related to Introduction to Statistical Relational Learning.   

Privacy in Social Networks

Elena Zheleva, Evimaria Terzi, Lise Getoor - Computers - 2012 - 75 pages
This synthesis lecture provides a survey of work on privacy in online social networks (OSNs). This work encompasses concerns of users as well as service providers and third ...
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An Inductive Logic Programming Approach to Statistical Relational Learning

Kristian Kersting - Computers - 2006 - 228 pages
"In his publication, the author Kristian Kersting has made an assault on one of the hardest integration problems at the heart of Artificial Intelligence research. This involves ...
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Markov Logic: An Interface Layer for Artificial Intelligence

Pedro Domingos, Daniel Lowd - Computers - 2009 - 145 pages
Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this is key to their success (e.g., the Internet in ...
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Probabilistic Inductive Logic Programming

Luc De Raedt, Paolo Frasconi, Kristian Kersting, Stephen H. Muggleton - Computers - 2008 - 341 pages
This book provides an introduction to probabilistic inductive logic programming. It places emphasis on the methods based on logic programming principles and covers formalisms ...
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Probabilistic Graphical Models: Principles and Techniques

Daphne Koller, Nir Friedman - Computers - 2009 - 1231 pages
A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.
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Inductive Logic Programming: 15th International Conference, ILP 2005, Bonn ...

Stefan Kramer, Bernhard Pfahringer - Computers - 2005 - 425 pages
This book constitutes the refereed proceedings of the 15th International Conference on Inductive Logic Programming, ILP 2005, held in Bonn, Germany, in August 2005. The 24 ...
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Probabilistic Graphical Models: Principles and Applications

Luis Enrique Sucar - Computers - 2015 - 253 pages
This accessible text/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. The book covers the fundamentals for ...
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