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» Wavelet Neural Networks with a Hybrid Learning Approach
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IJCNN
2006
IEEE
15 years 5 months ago
Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...
IPPS
1998
IEEE
15 years 4 months ago
Using the BSP Cost Model to Optimise Parallel Neural Network Training
We derive cost formulae for three di erent parallelisation techniques for training supervised networks. These formulae are parameterised by properties of the target computer archit...
R. O. Rogers, David B. Skillicorn
IJCAI
2001
15 years 1 months ago
Learning Iterative Image Reconstruction
Successful image reconstruction requires the recognition of a scene and the generation of a clean image of that scene. We propose to use recurrent neural networks for both analysi...
Sven Behnke
TSMC
1998
91views more  TSMC 1998»
14 years 11 months ago
Toward the border between neural and Markovian paradigms
— A new tendency in the design of modern signal processing methods is the creation of hybrid algorithms. This paper gives an overview of different signal processing algorithms si...
Piotr Wilinski, Basel Solaiman, A. Hillion, W. Cza...
BMCBI
2007
186views more  BMCBI 2007»
14 years 12 months ago
Modeling human cancer-related regulatory modules by GA-RNN hybrid algorithms
Background: Modeling cancer-related regulatory modules from gene expression profiling of cancer tissues is expected to contribute to our understanding of cancer biology as well as...
Jung-Hsien Chiang, Shih-Yi Chao