English(EN) A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks

新理论解释了部分训练神经网络的训练动力学

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-08 04:00

研究人员开发了一个新的理论框架，以理解部分训练的三层神经网络的训练动力学。通过将平均场理论扩展到函数空间，他们证明了极限模型遵循具有时变核的函数梯度流。这种方法证明了训练损失的线性收敛，并展示了跨不同缩放机制下的特征学习。 AI

影响为神经网络训练提供了理论见解，可能为未来的模型开发和优化策略提供信息。

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arXiv stat.ML TIER_1 English(EN) · Zhengdao Chen, Eric Vanden-Eijnden, Joan Bruna · 2026-07-08 04:00

部分训练的三层神经网络的函数空间平均场理论

arXiv:2210.16286v2 Announce Type: replace-cross Abstract: To understand the training dynamics of neural networks, prior studies have considered the mean-field limit of two-layer neural networks as the width tends to infinity, establishing theoretical guarantees for its convergenc…