English(EN) Mean-Field Model for Two-Layer Neural Networks Trained with Consensus-Based Optimization

新的均场模型通过基于共识的优化增强了神经网络训练

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-01 04:00

研究人员开发了一种用于使用基于共识的优化（CBO）训练两层神经网络的均场模型。该方法与Adam结合使用时，比单独使用CBO收敛更快。研究还表明，CBO可以适应多任务学习，并减少内存开销。CBO和神经网络的均场模型均已通过数值计算得到验证。 AI

影响引入了一种新颖的优化技术，有望提高神经网络训练的效率。

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arXiv cs.LG TIER_1 English(EN) · William De Deyn, Michael Herty, Giovanni Samaey · 2026-07-01 04:00

用于通过基于共识的优化训练的两层神经网络的均场模型

arXiv:2511.21466v3 Announce Type: replace Abstract: We study Consensus-Based Optimization (CBO) for two-layer neural network training. We compare the performance of CBO against Adam on two test cases and demonstrate how a hybrid approach, combining CBO with Adam, provides faster …