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Andrew Dienstfrey (Fed)

Publications

Layer ensemble averaging for fault tolerance in memristive neural networks

Author(s)
Osama Yousuf, Brian Hoskins, Karthick Ramu, Mitchell Fream, William Borders, Advait Madhavan, Matthew Daniels, Andrew Dienstfrey, Jabez McClelland, Martin Lueker-Boden, Gina Adam
Advancements in continual learning with artificial neural networks have been fueled in large part by scaling network dimensionalities. As this scaling continues
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Patents (2018-Present)

The figure illustrates a system for parameter multiplexed gradient descent in accordance with embodiments of the present invention.

System And Method For Parameter Multiplexed Gradient Descent

NIST Inventors
Adam McCaughan , Sonia Buckley and Andrew Dienstfrey
Parameter multiplexed gradient descent (PMGD) is a machine learning training method designed to easily train emergent non-volatile memory and neuromorphic hardware platforms.
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Created May 31, 2018, Updated December 8, 2022
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