144 citations · 325 across the 12 of their papers we have counts for
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cs.LG2022★ 12 cited
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning
Yujun Shi, Jian Liang, Wenqing Zhang +2
Federated learning aims to train models collaboratively across different clients without the sharing of data for privacy considerations. However, one major challenge for this learn…
cs.LG2021★ 3 cited
Continual Learning via Bit-Level Information Preserving
Yujun Shi, Li Yuan, Yunpeng Chen +1
Continual learning tackles the setting of learning different tasks sequentially. Despite the lots of previous solutions, most of them still suffer significant forgetting or expensi…
cs.LG2019★ 39 cited
Rethinking the Usage of Batch Normalization and Dropout in the Training of Deep Neural Networks
Guangyong Chen, Pengfei Chen, Yujun Shi +3
In this work, we propose a novel technique to boost training efficiency of a neural network. Our work is based on an excellent idea that whitening the inputs of neural networks can…