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ESANN
2003
13 years 10 months ago
Accelerating the convergence speed of neural networks learning methods using least squares
In this work a hybrid training scheme for the supervised learning of feedforward neural networks is presented. In the proposed method, the weights of the last layer are obtained em...
Oscar Fontenla-Romero, Deniz Erdogmus, José...
IJCNN
2006
IEEE
14 years 2 months ago
High-speed Bi-directional Function Approximation using Plausible Neural Networks
— This paper applies a recently developed neural network called plausible neural network (PNN) to function approximation. Instead of using error correction, PNN estimates the mut...
Kuo-Chen Li, Dar-Jen Chang, Yuan Yan Chen
ICNC
2005
Springer
14 years 2 months ago
Segmentation of SAR Image Using Mixture Multiscale ARMA Network
Abstract. A mixture multiscale autoregressive moving average (ARMA) network is proposed for unsupervised segmentation of synthetic aperture radar (SAR) image. The network combines ...
Haixia Xu, Tian Zheng, Fan Meng
TNN
2008
177views more  TNN 2008»
13 years 8 months ago
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model
Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
Yoshua Bengio, Jean-Sébastien Senecal
NIPS
1994
13 years 9 months ago
Active Learning with Statistical Models
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...