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» Probabilistic-Logic Models: Reasoning and Learning with Rela...
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FUIN
2008
108views more  FUIN 2008»
14 years 11 months ago
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-logic) is a probabilistic modeling language that is especially designed to express such rel...
Wannes Meert, Jan Struyf, Hendrik Blockeel
ILP
1999
Springer
15 years 5 months ago
Probabilistic Relational Models
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
Daphne Koller
AGI
2008
15 years 2 months ago
How Might Probabilistic Reasoning Emerge from the Brain?
: A series of hypotheses is proposed, connecting neural structures and dynamics with the formal structures and processes of probabilistic logic. First, a hypothetical connection is...
Ben Goertzel, Cassio Pennachin
CSL
2010
Springer
15 years 1 months ago
Randomisation and Derandomisation in Descriptive Complexity Theory
We study probabilistic complexity classes and questions of derandomisation from a logical point of view. For each logic L we introduce a new logic BPL, bounded error probabilistic ...
Kord Eickmeyer, Martin Grohe
ECML
2007
Springer
15 years 7 months ago
Structure Learning of Probabilistic Relational Models from Incomplete Relational Data
Abstract. Existing relational learning approaches usually work on complete relational data, but real-world data are often incomplete. This paper proposes the MGDA approach to learn...
Xiao-Lin Li, Zhi-Hua Zhou