3 papers
stat.ML2020
Convolutional Kernel Networks for Graph-Structured Data
Dexiong Chen, Laurent Jacob, Julien Mairal
We introduce a family of multilayer graph kernels and establish new links between graph convolutional neural networks and kernel methods. Our approach generalizes convolutional ker…
cs.CV2019
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning
Zhijun Mai, Guosheng Hu, Dexiong Chen +2
MixUp is an effective data augmentation method to regularize deep neural networks via random linear interpolations between pairs of samples and their labels. It plays an important…
stat.ML2019
Recurrent Kernel Networks
Dexiong Chen, Laurent Jacob, Julien Mairal
Substring kernels are classical tools for representing biological sequences or text. However, when large amounts of annotated data are available, models that allow end-to-end train…