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ICANN
2003
Springer
13 years 10 months ago
Meta-learning for Fast Incremental Learning
Model based learning systems usually face to a problem of forgetting as a result of the incremental learning of new instances. Normally, the systems have to re-learn past instances...
Takayuki Oohira, Koichiro Yamauchi, Takashi Omori
UAI
2003
13 years 6 months ago
Learning Module Networks
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
IPPS
2006
IEEE
13 years 11 months ago
Parallelization of module network structure learning and performance tuning on SMP
As an extension of Bayesian network, module network is an appropriate model for inferring causal network of a mass of variables from insufficient evidences. However learning such ...
Hongshan Jiang, Chunrong Lai, Wenguang Chen, Yuron...
BMCBI
2007
104views more  BMCBI 2007»
13 years 4 months ago
Validating module network learning algorithms using simulated data
Tom Michoel, Steven Maere, Eric Bonnet, Anagha Jos...
NIPS
2007
13 years 6 months ago
Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity
Reward-modulated spike-timing-dependent plasticity (STDP) has recently emerged as a candidate for a learning rule that could explain how local learning rules at single synapses su...
Robert A. Legenstein, Dejan Pecevski, Wolfgang Maa...