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NIPS
1992
15 years 3 months ago
Explanation-Based Neural Network Learning for Robot Control
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
Tom M. Mitchell, Sebastian Thrun
IJON
2008
109views more  IJON 2008»
15 years 1 months ago
Unsupervised learning neural network with convex constraint: Structure and algorithm
This paper proposed a kind of unsupervised learning neural network model, which has special structure and can realize an evaluation and classification of many groups by the compres...
Hengqing Tong, Tianzhen Liu, Qiaoling Tong
ICAISC
2004
Springer
15 years 7 months ago
Visualization of Hidden Node Activity in Neural Networks: II. Application to RBF Networks
Scatterograms of the images of training set vectors in the hidden space help to evaluate the quality of neural network mappings and understand internal representations created by t...
Wlodzislaw Duch
ISNN
2005
Springer
15 years 7 months ago
Enhanced Fuzzy Single Layer Perceptron
Abstract. In this paper, a method of improving the learning time and convergence rate is proposed to exploit the advantages of artificial neural networks and fuzzy theory to neuron...
Kwang-Baek Kim, Sungshin Kim, Young Hoon Joo, Am S...
CEC
2008
IEEE
15 years 8 months ago
Learning what to ignore: Memetic climbing in topology and weight space
— We present the memetic climber, a simple search algorithm that learns topology and weights of neural networks on different time scales. When applied to the problem of learning ...
Julian Togelius, Faustino J. Gomez, Jürgen Sc...