163 citations · 452 across the 26 of their papers we have counts for
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cs.LG2023
Steering Prototypes with Prompt-tuning for Rehearsal-free Continual Learning
Zhuowei Li, Long Zhao, Zizhao Zhang +4
In the context of continual learning, prototypes-as representative class embeddings-offer advantages in memory conservation and the mitigation of catastrophic forgetting. However,…
cs.LG2022★ 13 cited
Surrogate Gap Minimization Improves Sharpness-Aware Training
Juntang Zhuang, Boqing Gong, Liangzhe Yuan +6
The recently proposed Sharpness-Aware Minimization (SAM) improves generalization by minimizing a \textit{perturbed loss} defined as the maximum loss within a neighborhood in the pa…
cs.LG2020★ 64 cited
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness
Long Zhao, Ting Liu, Xi Peng +1
Adversarial data augmentation has shown promise for training robust deep neural networks against unforeseen data shifts or corruptions. However, it is difficult to define heuristic…