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» Probabilistic Inductive Logic Programming
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IDA
2005
Springer
13 years 10 months ago
Combining Bayesian Networks with Higher-Order Data Representations
Abstract. This paper introduces Higher-Order Bayesian Networks, a probabilistic reasoning formalism which combines the efficient reasoning mechanisms of Bayesian Networks with the...
Elias Gyftodimos, Peter A. Flach
ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 5 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
ILP
2007
Springer
13 years 11 months ago
Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates
Statistical Relational Learning (SRL) combines the benefits of probabilistic machine learning approaches with complex, structured domains from Inductive Logic Programming (ILP). W...
Mark Goadrich, Jude W. Shavlik
ICONIP
1998
13 years 6 months ago
Inducing Relational Concepts with Neural Networks via the LINUS System
This paper presents a method to induce relational concepts with neural networks using the inductive logic programming system LINUS. Some first-order inductive learning tasks taken...
Rodrigo Basilio, Gerson Zaverucha, Artur S. d'Avil...
LANMR
2004
13 years 6 months ago
New Semantics for Hybrid Probabilistic Programs
Hybrid probabilistic programs framework [5] is a variation of probabilistic annotated logic programming approach, which allows the user to explicitly encode the available knowledge...
Emad Saad