2024 "sharpness-aware minimization" Papers
11 papers found
A Universal Class of Sharpness-Aware Minimization Algorithms
Behrooz Tahmasebi, Ashkan Soleymani, Dara Bahri et al.
ICML 2024posterarXiv:2406.03682
Flatness-aware Sequential Learning Generates Resilient Backdoors
Hoang Pham, The-Anh Ta, Anh Tran et al.
ECCV 2024posterarXiv:2407.14738
1
citations
Forget Sharpness: Perturbed Forgetting of Model Biases Within SAM Dynamics
Ankit Vani, Frederick Tung, Gabriel Oliveira et al.
ICML 2024posterarXiv:2406.06700
How to Escape Sharp Minima with Random Perturbations
Kwangjun Ahn, Ali Jadbabaie, Suvrit Sra
ICML 2024posterarXiv:2305.15659
Improving SAM Requires Rethinking its Optimization Formulation
Wanyun Xie, Fabian Latorre, Kimon Antonakopoulos et al.
ICML 2024posterarXiv:2407.12993
Improving Sharpness-Aware Minimization by Lookahead
Runsheng Yu, Youzhi Zhang, James Kwok
ICML 2024poster
Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization
Ziqing Fan, Shengchao Hu, Jiangchao Yao et al.
ICML 2024spotlightarXiv:2405.18890
Lookbehind-SAM: k steps back, 1 step forward
Gonçalo Mordido, Pranshu Malviya, Aristide Baratin et al.
ICML 2024posterarXiv:2307.16704
On the Duality Between Sharpness-Aware Minimization and Adversarial Training
Yihao Zhang, Hangzhou He, Jingyu Zhu et al.
ICML 2024posterarXiv:2402.15152
Rethinking the Flat Minima Searching in Federated Learning
Taehwan Lee, Sung Whan Yoon
ICML 2024poster
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention
Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov et al.
ICML 2024posterarXiv:2402.10198