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IJAR
2006
89views more  IJAR 2006»
15 years 2 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
JCP
2007
121views more  JCP 2007»
15 years 2 months ago
Learning by Discrimination: A Constructive Incremental Approach
Abstract— This paper presents i-AA1 , a constructive, incremental learning algorithm for a special class of weightless, self-organizing networks. In i-AA1 , learning consists of ...
Christophe G. Giraud-Carrier, Tony R. Martinez
IJCNN
2006
IEEE
15 years 9 months ago
Optimal In-Place Learning and the Lobe Component Analysis
— It is difficult to map many existing learning algorithms onto biological networks because the former require a separate learning network. The computational basis of biological...
Juyang Weng, Nan Zhang 0002
AICT
2006
IEEE
15 years 9 months ago
Privacy and data protection in technology-enhanced professional learning
Privacy provision and data protection are basic requirements for professional learning, especially when personalized systems are used that adapt to sensitive learner personal data...
Tomaz Klobucar
ICALT
2006
IEEE
15 years 9 months ago
Social Software for Professional Learning: Examples and Research Issues
Social software is used widely in organizational knowledge management and professional learning. The PROLEARN network of excellence appreciates the trend of lowering the barriers ...
Ralf Klamma, Mohamed Amine Chatti, Erik Duval, Seb...