94 citations · 95 across the 2 of their papers we have counts for
2 papers
cs.LG2019★ 1 cited
An Empirical Study on Regularization of Deep Neural Networks by Local Rademacher Complexity
Yingzhen Yang, Jiahui Yu, Xingjian Li +2
Regularization of Deep Neural Networks (DNNs) for the sake of improving their generalization capability is important and challenging. The development in this line benefits theoreti…
cs.LG2019★ 94 cited
DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks
Xingjian Li, Haoyi Xiong, Hanchao Wang +4
Transfer learning through fine-tuning a pre-trained neural network with an extremely large dataset, such as ImageNet, can significantly accelerate training while the accuracy is fr…