标题 |
![]() 卷积神经网络中Hebbian学习的实现挑战和策略
相关领域
赫比理论
利布拉
计算机科学
人工智能
反向传播
人工神经网络
深度学习
卷积神经网络
机器学习
竞争性学习
无监督学习
唤醒睡眠算法
泛化误差
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其它 | Given the unprecedented growth of deep learning applications, training acceleration is becoming a subject of strong academic interest. Hebbian learning as a training strategy alternative to backpropagation presents a promising optimization approach due to its locality, lower computational complexity and parallelization potential. Nevertheless, due to the challenging optimization of Hebbian learning, there is no widely accepted approach to the implementation of such mixed strategies. The current paper overviews the 4 main strategies for updating weights using the Hebbian rule |
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