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» Evolving Multilayer Perceptrons
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JMLR
2012
11 years 10 months ago
Deep Learning Made Easier by Linear Transformations in Perceptrons
We transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut connections to model th...
Tapani Raiko, Harri Valpola, Yann LeCun
NIPS
2004
13 years 9 months ago
Unsupervised Variational Bayesian Learning of Nonlinear Models
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...
Antti Honkela, Harri Valpola
MVA
1990
101views Computer Vision» more  MVA 1990»
13 years 8 months ago
A Segmentation Free Approach to Symbol Extraction and Recognition from Image Document
: We present a symbol recognition method without segmentation of the document. Our approach uses Zernike moments for the coding and a multilayered Perceptron for the classifier. Re...
Maurice Milgram, Mattieu Jobert, Bertrand Lamy
CCE
2008
13 years 7 months ago
Differential recurrent neural network based predictive control
An efficient algorithm to train general differential recurrent neural networks is proposed. The trained network can be directly used as the internal model of a predictive controll...
R. K. Al Seyab, Yi Cao
CORR
2008
Springer
127views Education» more  CORR 2008»
13 years 7 months ago
Intrusion Detection in Mobile Ad Hoc Networks Using Classification Algorithms
In this paper we present the design and evaluation of intrusion detection models for MANETs using supervised classification algorithms. Specifically, we evaluate the performance of...
Aikaterini Mitrokotsa, Manolis Tsagkaris, Christos...