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Siqi Mai

2 accepted papers

2022

Random Sharpness-Aware Minimization

Yong Liu, Siqi Mai, Minhao Cheng, Xiangning Chen, Cho-Jui Hsieh, Yang You
NeurIPS 2022accept

Currently, Sharpness-Aware Minimization (SAM) is proposed to seek the parameters that lie in a flat region to improve the generalization when training neural networks. In particular, a minimax optimization objective is defined to find the maximum loss value centered on the weight, out of the purpose…

Cited by 33Source ↗PDF ↗Scholar ↗
2022

Towards Efficient and Scalable Sharpness-Aware Minimization

Yong Liu, Siqi Mai, Xiangning Chen, Cho-Jui Hsieh, Yang You
CVPR 2022poster

Recently, Sharpness-Aware Minimization (SAM), which connects the geometry of the loss landscape and generalization, has demonstrated a significant performance boost on training large-scale models such as vision transformers. However, the update rule of SAM requires two sequential (non-parallelizable…

Cited by 152PDF ↗code ↗Scholar ↗