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Mar, 2024
无监督的端到端训练:自定义的生物启发目标
Unsupervised End-to-End Training with a Self-Defined Bio-Inspired Target
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Dongshu Liu, Jérémie Laydevant, Adrien Pontlevy, Damien Querlioz, Julie Grollier
TL;DR
通过引入一种自定义目标和生物启发稳态机制,结合全局和局部学习规则,该研究提出了一种端到端无监督学习方法,在边缘人工智能硬件上表现出了较高的准确率,并展示了该方法在半监督学习中的应用潜力。
Abstract
Current
unsupervised learning
methods depend on end-to-end training via
deep learning
techniques such as self-supervised learning, with high computational requirements, or employ layer-by-layer training using bio
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