Model Generalization: A Sharpness Aware Optimization Perspective

التفاصيل البيبلوغرافية
العنوان: Model Generalization: A Sharpness Aware Optimization Perspective
المؤلفون: Coldenhoff, Jozef Marus, Li, Chengkun, Zhu, Yurui
سنة النشر: 2022
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
الوصف: Sharpness-Aware Minimization (SAM) and adaptive sharpness-aware minimization (ASAM) aim to improve the model generalization. And in this project, we proposed three experiments to valid their generalization from the sharpness aware perspective. And our experiments show that sharpness aware-based optimization techniques could help to provide models with strong generalization ability. Our experiments also show that ASAM could improve the generalization performance on un-normalized data, but further research is needed to confirm this.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2208.06915
رقم الأكسشن: edsarx.2208.06915
قاعدة البيانات: arXiv