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» Probabilistic-Logic Models: Reasoning and Learning with Rela...
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IJCAI
2007
15 years 5 months ago
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
ICALT
2005
IEEE
15 years 10 months ago
Flexible and Exploratory Learning by Polyscopic Topic Maps
Flexible and active education calls for a comprehensive restructuring of the traditional university course format. Such restructuring can be done in a natural and coherent way by ...
Dino Karabeg, Rolf Guescini, Tommy W. Nordeng
CORR
2010
Springer
116views Education» more  CORR 2010»
14 years 11 months ago
Mixed-Membership Stochastic Block-Models for Transactional Networks
Abstract: Transactional network data can be thought of as a list of oneto-many communications (e.g., email) between nodes in a social network. Most social network models convert th...
Mahdi Shafiei, Hugh Chipman
AGI
2008
15 years 5 months ago
Cognitive Primitives for Automated Learning
Artificial Intelligence deals with the automated simulation of human intelligent behavior. Various aspects of human faculties are tackled using computational models. It is clear th...
Sudharsan Iyengar
CVPR
2000
IEEE
15 years 8 months ago
Learning Patterns from Images by Combining Soft Decisions and Hard Decisions
We present a novel approach for learning patterns (sub-images) shared by multiple images without prior knowledge about the number and the positions of the patterns in the images. ...
Pengyu Hong, Thomas S. Huang, Roy Wang