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实体 Broken Ergodicity and the Violation of the Fluctuation-Dissipation Theorem Lead to Generalization Beyond Overfitting in Machine Learning

Broken Ergodicity and the Violation of the Fluctuation-Dissipation Theorem Lead to Generalization Beyond Overfitting in Machine Learning

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  1. TOOL · CL_137124 ·

    Machine learning double descent linked to superconducting transition physics

    一篇新论文探讨了机器学习中的“双下降”现象,即神经网络的泛化能力在其复杂度超过训练数据量时仍能继续提高。研究人员利用动力学平均场理论证明,这种行为源于控制训练过程的随机场论中的一个相变。该相变以遍历性破坏导致涨落耗散定理失效为特征,网络的泛化能力与超导转变的伦敦模型相似。