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» On the Use of Evidence in Neural Networks
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ML
2011
ACM
179views Machine Learning» more  ML 2011»
14 years 8 months ago
Neural networks for relational learning: an experimental comparison
In the last decade, connectionist models have been proposed that can process structured information directly. These methods, which are based on the use of graphs for the representa...
Werner Uwents, Gabriele Monfardini, Hendrik Blocke...
130
Voted
IPPS
2007
IEEE
15 years 8 months ago
Recurrent neural networks towards detection of SQL attacks
In the paper we present a new approach based on application of neural networks to detect SQL attacks. SQL attacks are those attacks that take advantage of using SQL statements to ...
Jaroslaw Skaruz, Franciszek Seredynski
SOFSEM
2004
Springer
15 years 7 months ago
Approaches Based on Markovian Architectural Bias in Recurrent Neural Networks
Recent studies show that state-space dynamics of randomly initialized recurrent neural network (RNN) has interesting and potentially useful properties even without training. More p...
Matej Makula, Michal Cernanský, Lubica Benu...
ICANN
2005
Springer
15 years 7 months ago
Batch-Sequential Algorithm for Neural Networks Trained with Entropic Criteria
The use of entropy as a cost function in the neural network learning phase usually implies that, in the back-propagation algorithm, the training is done in batch mode. Apart from t...
Jorge M. Santos, Joaquim Marques de Sá, Lu&...
DAGM
2007
Springer
15 years 5 months ago
Efficient Learning of Neural Networks with Evolutionary Algorithms
Abstract. In this article we present EANT2, a method that creates neural networks (NNs) by evolutionary reinforcement learning. The structure of NNs is developed using mutation ope...
Nils T. Siebel, Jochen Krause, Gerald Sommer