"sharpness-aware minimization" Papers
20 papers found
Conference
An Analysis of Concept Bottleneck Models: Measuring, Understanding, and Mitigating the Impact of Noisy Annotations
Seonghwan Park, Jueun Mun, Donghyun Oh et al.
FedWMSAM: Fast and Flat Federated Learning via Weighted Momentum and Sharpness-Aware Minimization
Tianle Li, Yongzhi Huang, Linshan Jiang et al.
Improving Model-Based Reinforcement Learning by Converging to Flatter Minima
Shrinivas Ramasubramanian, Benjamin Freed, Alexandre Capone et al.
Mitigating Parameter Interference in Model Merging via Sharpness-Aware Fine-Tuning
Yeoreum Lee, Jinwook Jung, Sungyong Baik
Modality-Aware SAM: Sharpness-Aware-Minimization Driven Gradient Modulation for Harmonized Multimodal Learning
Hossein Rajoli Nowdeh, Jie Ji, Xiaolong Ma et al.
Noise Stability Optimization for Finding Flat Minima: A Hessian-based Regularization Approach
Haotian Ju, Hongyang Zhang, Dongyue Li
Sharpness-Aware Minimization: General Analysis and Improved Rates
Dimitris Oikonomou, Nicolas Loizou
SharpZO: Hybrid Sharpness-Aware Vision Language Model Prompt Tuning via Forward-Only Passes
Yifan Yang, Zhen Zhang, Rupak Vignesh Swaminathan et al.
The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation
Yuhan Liu, Yixiong Zou, Yuhua Li et al.
A Universal Class of Sharpness-Aware Minimization Algorithms
Behrooz Tahmasebi, Ashkan Soleymani, Dara Bahri et al.
Flatness-aware Sequential Learning Generates Resilient Backdoors
Hoang Pham, The-Anh Ta, Anh Tran et al.
Forget Sharpness: Perturbed Forgetting of Model Biases Within SAM Dynamics
Ankit Vani, Frederick Tung, Gabriel Oliveira et al.
How to Escape Sharp Minima with Random Perturbations
Kwangjun Ahn, Ali Jadbabaie, Suvrit Sra
Improving SAM Requires Rethinking its Optimization Formulation
Wanyun Xie, Fabian Latorre, Kimon Antonakopoulos et al.
Improving Sharpness-Aware Minimization by Lookahead
Runsheng Yu, Youzhi Zhang, James Kwok
Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization
Ziqing Fan, Shengchao Hu, Jiangchao Yao et al.
Lookbehind-SAM: k steps back, 1 step forward
Gonçalo Mordido, Pranshu Malviya, Aristide Baratin et al.
On the Duality Between Sharpness-Aware Minimization and Adversarial Training
Yihao Zhang, Hangzhou He, Jingyu Zhu et al.
Rethinking the Flat Minima Searching in Federated Learning
Taehwan Lee, Sung Whan Yoon
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.