Learning with Delayed Synaptic Plasticity

22 Mar 2019Anil YamanGiovanni IaccaDecebal Constantin MocanuGeorge FletcherMykola Pechenizkiy

The plasticity property of biological neural networks allows them to perform learning and optimize their behavior by changing their configuration. Inspired by biology, plasticity can be modeled in artificial neural networks by using Hebbian learning rules, i.e. rules that update synapses based on the neuron activations and reinforcement signals... (read more)

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