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IJAR
2006
89views more  IJAR 2006»
15 years 7 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
DSS
2007
127views more  DSS 2007»
15 years 7 months ago
Large-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
PAMI
2006
127views more  PAMI 2006»
15 years 7 months ago
Incremental Nonlinear Dimensionality Reduction by Manifold Learning
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
Martin H. C. Law, Anil K. Jain
PR
2006
101views more  PR 2006»
15 years 7 months ago
Feature-based approach to semi-supervised similarity learning
For the management of digital document collections, automatic database analysis still has ties to deal with semantic queries and abstract concepts that users are looking for. When...
Philippe Henri Gosselin, Matthieu Cord
NN
2007
Springer
173views Neural Networks» more  NN 2007»
15 years 7 months ago
An enhanced self-organizing incremental neural network for online unsupervised learning
An enhanced self-organizing incremental neural network (ESOINN) is proposed to accomplish online unsupervised learning tasks. It improves the self-organizing incremental neural ne...
Shen Furao, Tomotaka Ogura, Osamu Hasegawa