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IJIT
2004
13 years 8 months ago
A Comparison of First and Second Order Training Algorithms for Artificial Neural Networks
Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no expli...
Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C...
JCP
2007
143views more  JCP 2007»
13 years 7 months ago
Noisy K Best-Paths for Approximate Dynamic Programming with Application to Portfolio Optimization
Abstract— We describe a general method to transform a non-Markovian sequential decision problem into a supervised learning problem using a K-bestpaths algorithm. We consider an a...
Nicolas Chapados, Yoshua Bengio
ICASSP
2011
IEEE
12 years 11 months ago
Recent development of discriminative training using non-uniform criteria for cross-level acoustic modeling
In this paper, we extend our previous study on discriminative training using non-uniform criteria for speech recognition. The work will put emphasis on how the acoustic modeling i...
Chao Weng, Biing-Hwang Juang
NC
2002
13 years 7 months ago
Parallel evolutionary training algorithms for "hardware-friendly" neural networks
In this paper, Parallel Evolutionary Algorithms for integer weight neural network training are presented. To this end, each processor is assigned a subpopulation of potential solut...
Vassilis P. Plagianakos, Michael N. Vrahatis
ISNN
2010
Springer
13 years 5 months ago
Pruning Training Samples Using a Supervised Clustering Algorithm
As practical pattern classification tasks are often very-large scale and serious imbalance such as patent classification, using traditional pattern classification techniques in ...
Minzhang Huang, Hai Zhao, Bao-Liang Lu