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cture with application to high-dimensional pattern recognition. In Biologically Inspired Cognitive Architec- tures, 2009. AAAI Press, 2009. ARKO9. I. Arel, D. Rose, and T. Karnowski. A deep learning architecture comprising homogeneous cortical circuits for scalable spatiotemporal pattern inference. NIP
Mathias. Optimization using disributed genetic algorithms. In Parallel Problem Solving from Nature, Edited by H Schwefel and R Manner, 1990. 5204. R. Sun and X. Zhang. Top-down versus bottom-up learning in cognitive skill acquisition. Cognitive Systems Research, 5, 2004. Tes59. Lucien TesniEre. Elem
Ami89. Daniel J. Amit. Modeling brain function - the world of attractor neural networks. Cambridge University Press, New York, USA, 1989. ARC09. I. Arel, D. Rose, and R. Coop. Destin: A scalable deep learning architecture with application to high-dimensional robust pattern recognition. Proc. AAA! Wor
2000. SV99. A. J. Storkey and R. Valabregue. The basins of attraction of a new hopfield learning rule. Neural Networks, 12:869-876, 1999. $204. R. Sun and X. 2hang. Top-down versus bottom-up learning in cognitive skill acquisition. Cognitive Systems Research, 5, 2004. TC97. M. Tomasello and .1. C
1. Ami89. Daniel J. Amit. Modeling brain function — the world of attractor neural networks. Cambridge University Press, New York, USA, 1989. ARCO9. I. Arel, D. Rose, and R. Coop. Destin: A scalable deep learning architecture with application to high-dimensional robust pattern recognition. Proc. AAAI Work
ub, 2000. SV99. A. J. Storkey and R. Valabregue. The basins of attraction of a new hopfield learning rule. Neural Networks, 12:869-876, 1999. SZ04, R. Sun and X. Zhang. Top-down versus bottom-up learning in cognitive skill acquisition. Cognitive Systems Research, 5, 2004. TC97. M. Tomasello and J. Call
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