163 search results - page 3 / 33 » Representing Aggregators in Relational Probabilistic Models |
ICMLA
2009
13 years 3 months ago
2009
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...
CORR
2010
Springer
13 years 6 months ago
2010
Springer
Incorporating probabilities into the semantics of incomplete databases has posed many challenges, forcing systems to sacrifice modeling power, scalability, or treatment of relatio...
ICML
2001
IEEE
14 years 6 months ago
2001
IEEE
Most real-world data is stored in relational form. In contrast, most statistical learning methods work with "flat" data representations, forcing us to convert our data i...
ILP
1999
Springer
13 years 10 months ago
1999
Springer
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
KR
2004
Springer
13 years 11 months ago
2004
Springer
To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilist...