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FLAIRS
2004
13 years 10 months ago
A Method Based on RBF-DDA Neural Networks for Improving Novelty Detection in Time Series
Novelty detection in time series is an important problem with application in different domains such as machine failure detection, fraud detection and auditing. An approach to this...
Adriano L. I. Oliveira, Fernando Buarque de Lima N...
IJCINI
2007
110views more  IJCINI 2007»
13 years 8 months ago
Toward Autonomic Computing: Adaptive Neural Network for Trajectory Planning
: The theme of this issue of IJCINI is on cognitive mechanisms of autonomic computing and laws of human cooperative work organization. This editorial addresses key notions of this ...
Amar Ramdane-Cherif
EUROCOLT
1997
Springer
14 years 26 days ago
Vapnik-Chervonenkis Dimension of Recurrent Neural Networks
Most of the work on the Vapnik-Chervonenkis dimension of neural networks has been focused on feedforward networks. However, recurrent networks are also widely used in learning app...
Pascal Koiran, Eduardo D. Sontag
TSMC
2008
164views more  TSMC 2008»
13 years 8 months ago
Bagging and Boosting Negatively Correlated Neural Networks
In this paper, we propose two cooperative ensemble learning algorithms, i.e., NegBagg and NegBoost, for designing neural network (NN) ensembles. The proposed algorithms incremental...
Md. Monirul Islam, Xin Yao, S. M. Shahriar Nirjon,...
IWANN
2005
Springer
14 years 2 months ago
Co-evolutionary Learning in Liquid Architectures
A large class of problems requires real-time processing of complex temporal inputs in real-time. These are difficult tasks for state-of-the-art techniques, since they require captu...
Igal Raichelgauz, Karina Odinaev, Yehoshua Y. Zeev...