FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level

Learning algorithms for Deep Neural Networks are typically based on supervised end-to-end Stochastic Gradient Descent (SGD) training with error backpropagation (backprop). Backprop algorithms require a large number of labelled training samples to achieve high performance. However, in many realistic...

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Veröffentlicht in:	arXiv.org 2022-07
Hauptverfasser:	Lagani, Gabriele, Gennaro, Claudio, Fassold, Hannes, Amato, Giuseppe
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Back propagation Back propagation networks Computer vision Machine learning Multiplication Neural networks Training
Online-Zugang:	Volltext
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