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omputing, 10:251-276, 1998. ANOO. Shun-ichi Amari and Hiroshi Nagaoka. Methods of information geometry. ANIS, 2000. ARC09a. I. Aral, D. Rose, and R. Coop. Destin: A scalable deep learning architecture with application to high-dimensional robust pattern recognition. Proc. AAA! Workshop on Biologically
tions, this refers to a software server that performs "offline" learning tasks (e.g. using MOSES or hilIclimbing), and is in communica- tion with an Operational Agent Controller software server that performs real-time agent control and dispatches learning tasks to and receives results from the Learning Serve
t. 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! Workshop on Biologically
tions, this refers to a software server that performs "offline" learning tasks (e.g. using MOSES or hilIclimbing), and is in communica- tion with an Operational Agent Controller software server that performs real-time agent control and dispatches learning tasks to and receives results from the Learning Serve
mit. 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 Workshop on Biologically I
ations, this refers to a software server that performs “offline” learning tasks (e.g. using MOSES or hillclimbing), and is in communica- tion with an Operational Agent Controller software server that performs real-time agent control and dispatches learning tasks to and receives results from the Learning Server
Entities connected to both R. Coop and Operational
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ORGANIZATIONBoolean SATisfaction
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ORGANIZATIONHebbian Learning
ORGANIZATIONChainer
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ORGANIZATIONSleator and Temperley
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