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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
9. Association for Computational Linguistics. Pei34. C. Peirce. Collected papers: Volume V. Pragmatism end pragmaticism. Harvard University Press. Cambridge MA., 1934. Pel05. Martin Pelikan. Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms. Springer, 2005.
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
to Artificial Intelligence. Springer, 1982. Pei34. C. Peirce. Collected papers: Volume V. Pragmatism and pragmaticism. Harvard University Press. Cambridge MA., 1934. Pe105. Martin Pelikan. Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms. Springer, 2005.
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
oach to Artificial Intelligence. Springer, 1982. Pei34. C, Peirce. Collected papers: Volume V. Pragmatism and pragmaticism. Harvard University Press. Cambridge MA., 1934. Pel05. Martin Pelikan. Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms. Springer, 2005. Pen9
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