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ESANN
2008
15 years 1 months ago
Learning Data Representations with Sparse Coding Neural Gas
Abstract. We consider the problem of learning an unknown (overcomplete) basis from an unknown sparse linear combination. Introducing the "sparse coding neural gas" algori...
Kai Labusch, Erhardt Barth, Thomas Martinetz
IJCNN
2006
IEEE
15 years 5 months ago
Learning using Dynamical Regime Identification and Synchronization
—This study proposes to generalize Hebbian learning by identifying and synchronizing the dynamical regimes of individual nodes in a recurrent network. The connection weights are ...
Nicolas Brodu
IJCAI
2007
15 years 1 months ago
Direct Code Access in Self-Organizing Neural Networks for Reinforcement Learning
TD-FALCON is a self-organizing neural network that incorporates Temporal Difference (TD) methods for reinforcement learning. Despite the advantages of fast and stable learning, TD...
Ah-Hwee Tan
ICDAR
2009
IEEE
15 years 6 months ago
Error-Correcting Output Coding for the Convolutional Neural Network for Optical Character Recognition
It is known that convolutional neural networks (CNNs) are efficient for optical character recognition (OCR) and many other visual classification tasks. This paper applies error-co...
Huiqun Deng, George Stathopoulos, Ching Y. Suen
NECO
2008
129views more  NECO 2008»
14 years 11 months ago
Sparse Coding via Thresholding and Local Competition in Neural Circuits
While evidence indicates that neural systems may be employing sparse approximations to represent sensed stimuli, the mechanisms underlying this ability are not understood. We desc...
Christopher J. Rozell, Don H. Johnson, Richard G. ...