标题 |
Implementation Challenges and Strategies for Hebbian Learning in Convolutional Neural Networks
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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