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» Learning grammatical structure with Echo State Networks
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ISDA
2008
IEEE
14 years 2 months ago
Combining Clustering and Bayesian Network for Gene Network Inference
Gene network reconstruction is a multidisciplinary research area involving data mining, machine learning, statistics, ontologies and others. Reconstructed gene network allows us t...
Suhaila Zainudin, Safaai Deris
JMLR
2010
137views more  JMLR 2010»
13 years 2 months ago
Importance Sampling for Continuous Time Bayesian Networks
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
Yu Fan, Jing Xu, Christian R. Shelton
IWANN
2005
Springer
14 years 1 months ago
Co-evolutionary Learning in Liquid Architectures
A large class of problems requires real-time processing of complex temporal inputs in real-time. These are difficult tasks for state-of-the-art techniques, since they require captu...
Igal Raichelgauz, Karina Odinaev, Yehoshua Y. Zeev...
ICDCS
2007
IEEE
14 years 2 months ago
Testing Security Properties of Protocol Implementations - a Machine Learning Based Approach
Security and reliability of network protocol implementations are essential for communication services. Most of the approaches for verifying security and reliability, such as forma...
Guoqiang Shu, David Lee
NN
2002
Springer
115views Neural Networks» more  NN 2002»
13 years 7 months ago
A self-organising network that grows when required
The ability to grow extra nodes is a potentially useful facility for a self-organising neural network. A network that can add nodes into its map space can approximate the input sp...
Stephen Marsland, Jonathan Shapiro, Ulrich Nehmzow