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ICONIP
1998
14 years 11 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...
KI
2010
Springer
14 years 8 months ago
Soft Evidential Update via Markov Chain Monte Carlo Inference
The key task in probabilistic reasoning is to appropriately update one’s beliefs as one obtains new information in the form of evidence. In many application settings, however, th...
Dominik Jain, Michael Beetz
CPE
2003
Springer
149views Hardware» more  CPE 2003»
15 years 2 months ago
Logical and Stochastic Modeling with SMART
We describe the main features of SmArT, a software package providing a seamless environment for the logic and probabilistic analysis of complex systems. SmArT can combine differen...
Gianfranco Ciardo, R. L. Jones III, Andrew S. Mine...
APIN
1999
110views more  APIN 1999»
14 years 9 months ago
The Connectionist Inductive Learning and Logic Programming System
The Connectionist Inductive Learning and Logic Programming System, C-IL 2 P, integrates the symbolic and connectionist paradigms of Artificial Intelligence through neural networks...
Artur S. d'Avila Garcez, Gerson Zaverucha
FGR
2008
IEEE
346views Biometrics» more  FGR 2008»
15 years 4 months ago
Markov random field models for hair and face segmentation
This paper presents an algorithm for measuring hair and face appearance in 2D images. Our approach starts by using learned mixture models of color and location information to sugg...
Kuang-chih Lee, Dragomir Anguelov, Baris Sumengen,...