Work-in-progress: what to expect of early training statistics? An investigation on hardware-aware 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: Conference or Workshop Item
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Neural Architecture Search; Early Training Statistics
• Online Access: https://hdl.handle.net/10356/165389
• Institution: Nanyang Technological University

Neural architecture search (NAS) is an emerging paradigm to automate the design of top-performing deep neural networks (DNNs). Specifically, the increasing success of NAS is attributed to the reliable performance estimation of different architectures. Despite significant progress to date, previous r...