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

• Main Authors: Luo, Xiangzhong, Liu, Di, Kong, Hao, Huai, Shuo, Chen, Hui, Liu, Weichen
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Neural Architecture Search; Hardware Performance Prediction
• Online Access: https://hdl.handle.net/10356/165388
• Institution: Nanyang Technological University

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,...