Neuromorphic Hardware Learns to Learn

Neuromorphic Hardware Learns to Learn

Hyperparameters and learning algorithms for neuromorphic hardware are usually chosen by hand to suit a particular task. In contrast, networks of neurons in the brain were optimized through extensive evolutionary and developmental processes to work well on a range of computing and learning tasks. Occ...

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Bibliographic Details
Main Authors: Thomas Bohnstingl, Franz Scherr, Christian Pehle, Karlheinz Meier, Wolfgang Maass
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-05-01
Series:Frontiers in Neuroscience
Subjects:
spiking neural networks
learning-to-learn
markov decision processes
multi-armed bandits
neuromorphic hardware
HICANN-DLS
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2019.00483/full

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https://www.frontiersin.org/article/10.3389/fnins.2019.00483/full

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