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Data
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Supervised learning with predictive coding (Whittington & Bogacz 2017)
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James Whittington
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"To effciently learn from feedback, cortical networks need to update synaptic weights
on multiple levels of cortical hierarchy. An effective and well-known algorithm for
computing such changes in synaptic weights is the error back-propagation algorithm. However, in the back-propagation algorithm, the change in synaptic weights
is a complex function of weights and activities of neurons not directly connected
with the synapse being modified, whereas the changes in biological synapses are
determined only by the activity of pre-synaptic and post-synaptic neurons. Several
models have been proposed that approximate the back-propagation algorithm with
local synaptic plasticity, but these models require complex external control over the
network or relatively complex plasticity rules. Here we show that a network developed in the predictive coding framework can efficiently perform supervised learning
fully autonomously, employing only simple local Hebbian plasticity. ..."
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Whittington, James C.R. [jcrwhittington at gmail.com] Show
Other
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jcrwhittington@googlemail.com
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