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» On the Use of Evidence in Neural Networks
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TNN
2008
177views more  TNN 2008»
15 years 1 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
IJCAI
2001
15 years 2 months ago
Genetic Algorithm based Selective Neural Network Ensemble
Neural network ensemble is a learning paradigm where several neural networks are jointly used to solve a problem. In this paper, the relationship between the generalization abilit...
Zhi-Hua Zhou, Jianxin Wu, Yuan Jiang, Shifu Chen
ICANN
2009
Springer
15 years 8 months ago
Almost Random Projection Machine
Backpropagation of errors is not only hard to justify from biological perspective but also it fails to solve problems requiring complex logic. A simpler algorithm based on generati...
Wlodzislaw Duch, Tomasz Maszczyk
IWANN
1997
Springer
15 years 5 months ago
The Pattern Extraction Architecture: A Connectionist Alternative to the Von Neumann Architecture
A detailed connectionist architecture is described which is capable of relating psychological behavior to the functioning of neurons and neurochemicals. The need to be able to bui...
L. Andrew Coward
ICAPR
2001
Springer
15 years 6 months ago
Pattern Matching and Neural Networks Based Hybrid Forecasting System
In this paper we propose a Neural Net-PMRS hybrid for forecasting time-series data. The neural network model uses the traditional MLP architecture and backpropagation method of tr...
Sameer Singh, Jonathan E. Fieldsend