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Learning With Markov Logic Networks


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Author by : Lilyana Simeonova Mihalkova
Languange Used : en
Release Date : 2009
Publisher by :

Traditionally, machine learning algorithms assume that training data is provided as a set of independent instances, each of which can be described as a feature vector. In contrast, many domains of int

Probabilistic Inductive Logic Programming


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Author by : Luc De Raedt
Languange Used : en
Release Date : 2008-03-14
Publisher by : Springer Science & Business Media

The question, how to combine probability and logic with learning, is getting an increased attention in several disciplines such as knowledge representation, reasoning about uncertainty, data mining, a

Discriminative Learning With Markov Logic Networks


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Languange Used : en
Release Date : 2009
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Statistical relational learning (SRL) is an emerging area of research that addresses the problem of learning from noisy structured/relational data. Markov logic networks (MLNs), sets of weighted claus

Inductive Logic Programming


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Author by : Filip Železný
Languange Used : en
Release Date : 2008-09-05
Publisher by : Springer Science & Business Media

This book constitutes the refereed proceedings of the 18th International Conference on Inductive Logic Programming, ILP 2008, held in Prague, Czech Republic, in September 2008. The 20 revised full pap

Ki 2007 Advances In Artificial Intelligence


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Author by : Joachim Hertzberg
Languange Used : en
Release Date : 2007-08-30
Publisher by : Springer Science & Business Media

The 30th Annual German Conference on Arti?cial Intelligence (KI-2007) took place in the University of Osnabru ̈ck, September 10–13, 2007. In this volume, you will ?nd papers or abstracts of its six