English(EN) OUIDecay: Adaptive Layer-wise Weight Decay for CNNs Using Online Activation Patterns

新的OUIDecay方法逐层自适应CNN正则化

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-11 08:08

研究人员推出了一种新颖的卷积神经网络自适应权重衰减方法OUIDecay。该技术根据在线激活模式动态调整每层的正则化强度，旨在提高训练效率和性能。与现有方法不同，OUIDecay不需要验证集，并在多个基准数据集和网络架构上展示了卓越的结果。 AI

影响引入了一种更有效、更强大的CNN正则化技术，有望提高模型性能并减少训练数据需求。

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arXiv cs.LG TIER_1 English(EN) · Enrique S. Quintana-Ortí · 2026-05-11 08:08

OUIDecay：使用在线激活模式对CNN进行自适应层级权重衰减

Weight decay remains one of the most widely used regularization mechanisms for training convolutional neural networks, yet it is still commonly applied as a fixed coefficient shared by all layers throughout training. This uniform treatment ignores that different layers may follow…