Towards interpretable deep local learning with successive gradient reconciliation
Relieving the reliance of neural network training on a global back-propagation (BP) has emerged as a notable research topic due to the biological implausibility and huge memory consumption caused by BP. Among the existing solutions, local learning optimizes gradient-isolated modules of a neural netw...
| Hlavní autoři: | , , , , , , |
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| Médium: | Conference item |
| Jazyk: | English |
| Vydáno: |
PMLR
2024
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