10 citations · 14 across the 6 of their papers we have counts for
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cs.LG2025
Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization
Chengli Tan, Yubo Zhou, Haishan Ye +7
Deep neural networks have been increasingly used in safety-critical applications such as medical diagnosis and autonomous driving. However, many studies suggest that they are prone…
cs.LG2024
Stabilizing Sharpness-aware Minimization Through A Simple Renormalization Strategy
Chengli Tan, Jiangshe Zhang, Junmin Liu +2
Recently, sharpness-aware minimization (SAM) has attracted much attention because of its surprising effectiveness in improving generalization performance. However, compared to stoc…
cs.LG2022
Learning Non-Vacuous Generalization Bounds from Optimization
Chengli Tan, Jiangshe Zhang, Junmin Liu +1
One of the fundamental challenges in the deep learning community is to theoretically understand how well a deep neural network generalizes to unseen data. However, current approach…