Systematic review of training-free neural architecture search: research progress, core challenges, and future directions
Neural Architecture Search (NAS) serves as a performance engine for automated machine learning, driving intelligent advancements across various domains. However, its development has been significantly constrained by the prohibitively high computational costs involved. Training-Free Neural Architecture Search (TFNAS)...