540 citations · 641 across the 6 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2021
Generalizing Neural Networks by Reflecting Deviating Data in Production
Yan Xiao, Yun Lin, Ivan Beschastnikh +3
Trained with a sufficiently large training and testing dataset, Deep Neural Networks (DNNs) are expected to generalize. However, inputs may deviate from the training dataset distri…
cs.LG2019★ 540 cited
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks
Zhi-Qin John Xu, Yaoyu Zhang, Tao Luo +2
We study the training process of Deep Neural Networks (DNNs) from the Fourier analysis perspective. We demonstrate a very universal Frequency Principle (F-Principle) -- DNNs often…
cs.LG2018★ 47 cited
Training behavior of deep neural network in frequency domain
Zhi-Qin John Xu, Yaoyu Zhang, Yanyang Xiao
Why deep neural networks (DNNs) capable of overfitting often generalize well in practice is a mystery [#zhang2016understanding]. To find a potential mechanism, we focus on the stud…