SurgeNAS: a comprehensive surgery on hardware-aware differentiable neural architecture search

• المؤلفون الرئيسيون: Luo, Xiangzhong, Liu, Di, Kong, Hao, Huai, Shuo, Chen, Hui, Liu, Weichen
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Computer science and engineering; Neural Architecture Search; Hardware Performance Prediction
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/165388

Differentiable neural architecture search (NAS) is an emerging paradigm to automate the design of top-performing convolutional neural networks (CNNs). However, previous differentiable NAS methods suffer from several crucial weaknesses, such as inaccurate gradient estimation, high memory consumption,...