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Jun, 2020
运用 Koopman 模态分析于神经网络
Applications of Koopman Mode Analysis to Neural Networks
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Iva Manojlović, Maria Fonoberova, Ryan Mohr, Aleksandr Andrejčuk, Zlatko Drmač...
TL;DR
本研究利用 Koopman 操作符对神经网络的训练过程进行研究,通过监控其谱和模态实现确定网络深度、优化初始化、减少噪音干扰和提升鲁棒性,并探究以负 Sobolev 规范为基础的损失函数在恢复受极大噪音污染的信号方面的应用。
Abstract
We consider the
training process
of a
neural network
as a
dynamical system
acting on the high-dimensional weight space. Each epoch is an a
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