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ISNN
2005
Springer
14 years 2 months ago
Post-nonlinear Blind Source Separation Using Neural Networks with Sandwiched Structure
Abstract. This paper proposes a novel algorithm based on informax for postnonlinear blind source separation. The demixing system culminates to a neural network with sandwiched stru...
Chunhou Zheng, Deshuang Huang, Zhan-Li Sun, Li Sha...
ESANN
2006
13 years 10 months ago
Visual object classification by sparse convolutional neural networks
Abstract. A convolutional network architecture termed sparse convolutional neural network (SCNN) is proposed and tested on a real-world classification task (car classification). In...
Alexander Gepperth
BC
2006
105views more  BC 2006»
13 years 9 months ago
A stochastic population approach to the problem of stable recruitment hierarchies in spiking neural networks
Recruitment learning in hierarchies is an inherently unstable process (Valiant, 1994). This paper presents conditions on parameters for a feedforward network to ensure stable recru...
Cengiz Günay, Anthony S. Maida
NECO
2010
101views more  NECO 2010»
13 years 4 months ago
Large-Margin Classification in Infinite Neural Networks
We introduce a new family of positive-definite kernels for large margin classification in support vector machines (SVMs). These kernels mimic the computation in large neural netwo...
Youngmin Cho, Lawrence K. Saul
AGI
2011
13 years 28 days ago
Systematically Grounding Language through Vision in a Deep, Recurrent Neural Network
Human intelligence consists largely of the ability to recognize and exploit structural systematicity in the world, relating our senses simultaneously to each other and to our cogni...
Derek Monner, James A. Reggia