%0 Generic %1 wang2019frequency %A Wang, Haohan %A Wu, Xindi %A Huang, Zeyi %A Xing, Eric P. %D 2019 %K 2019 cnn deep-learning %T High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks %U http://arxiv.org/abs/1905.13545 %X We investigate the relationship between the frequency spectrum of image data and the generalization behavior of convolutional neural networks (CNN). We first notice CNN's ability in capturing the high-frequency components of images. These high-frequency components are almost imperceptible to a human. Thus the observation leads to multiple hypotheses that are related to the generalization behaviors of CNN, including a potential explanation for adversarial examples, a discussion of CNN's trade-off between robustness and accuracy, and some evidence in understanding training heuristics. Our observation also immediately inspire methods related to the adversarial attack and defense methods.

@misc{wang2019frequency, abstract = {We investigate the relationship between the frequency spectrum of image data and the generalization behavior of convolutional neural networks (CNN). We first notice CNN's ability in capturing the high-frequency components of images. These high-frequency components are almost imperceptible to a human. Thus the observation leads to multiple hypotheses that are related to the generalization behaviors of CNN, including a potential explanation for adversarial examples, a discussion of CNN's trade-off between robustness and accuracy, and some evidence in understanding training heuristics. Our observation also immediately inspire methods related to the adversarial attack and defense methods.}, added-at = {2020-01-07T19:58:19.000+0100}, author = {Wang, Haohan and Wu, Xindi and Huang, Zeyi and Xing, Eric P.}, biburl = {https://www.bibsonomy.org/bibtex/2f60917704cf78781b612c3430d2c3121/analyst}, description = {[1905.13545] High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks}, interhash = {3756e3a9e44005276d47f3faec5a2a4d}, intrahash = {f60917704cf78781b612c3430d2c3121}, keywords = {2019 cnn deep-learning}, note = {cite arxiv:1905.13545}, timestamp = {2020-01-07T19:58:19.000+0100}, title = {High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks}, url = {http://arxiv.org/abs/1905.13545}, year = 2019 }