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ICDAR
2003
IEEE
15 years 3 months ago
Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis
Neural networks are a powerful technology for classification of visual inputs arising from documents. However, there is a confusing plethora of different neural network methods th...
Patrice Simard, David Steinkraus, John C. Platt
GECCO
2008
Springer
118views Optimization» more  GECCO 2008»
14 years 11 months ago
Unsupervised learning of echo state networks: balancing the double pole
A possible alternative to fine topology tuning for Neural Network (NN) optimization is to use Echo State Networks (ESNs), recurrent NNs built upon a large reservoir of sparsely r...
Fei Jiang, Hugues Berry, Marc Schoenauer
60
Voted
ESANN
2007
14 years 11 months ago
Informational cost in correlation-based neuronal networks
The cost of maintaining a given level of activity in a neuronal network depends on its size and degree of connectivity. Should a neural function require large-size fully-connected ...
Gaetano Liborio Aiello, Carlo Casarino
ICANN
2009
Springer
15 years 4 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
IJCNN
2000
IEEE
15 years 2 months ago
Applying CMAC-Based On-Line Learning to Intrusion Detection
The timely and accurate detection of computer and network system intrusions has always been an elusive goal for system administrators and information security researchers. Existin...
James Cannady