Original paper

Local online learning in recurrent networks with random feedback

eLife7.70
Volume: 8
Published: May 24, 2019
Abstract
Recurrent neural networks (RNNs) enable the production and processing of time-dependent signals such as those involved in movement or working memory. Classic gradient-based algorithms for training RNNs have been available for decades, but are inconsistent with biological features of the brain, such as causality and locality. We derive an approximation to gradient-based learning that comports with these constraints by requiring synaptic weight...
Paper Details
Title
Local online learning in recurrent networks with random feedback
Published Date
May 24, 2019
Journal
Volume
8
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