Putting An End to End-to-End: Gradient-Isolated Learning of Representations

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), (2019): 3033-3045

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We propose a novel deep learning method for local self-supervised representation learning that does not require labels nor end-to-end backpropagation but exploits the natural order in data instead. Inspired by the observation that biological neural networks appear to learn without backpropagating a global error signal, we split a deep neu...更多

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Sindy Löwe
Sindy Löwe
Peter O'Connor
Peter O'Connor
Bastiaan Veeling
Bastiaan Veeling
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