Gradient-based boosting for statistical relational learning: the relational dependency network case

Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are graphical models that extend dependency networks to relational domains. This higher expressivity, however, comes at the...

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Veröffentlicht in:	Machine Learning 2012, Vol.86 (1), p.25-56
Hauptverfasser:	Natarajan, Sriraam, Khot, Tushar, Kersting, Kristian, Gutmann, Bernd, Shavlik, Jude
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
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