Many societal and industrial problem-solving tasks involving search, optimization, design, and management are conveniently decomposed into hierarchical subproblems. While this process allows a syst…
Neural architecture search (NAS) has been widely studied to design high-performance network architectures automatically. However, existing approaches require more search time and substantial resour…
Neural architecture search (NAS) has emerged as a promising avenue for automatically designing task-specific neural networks. Existing NAS approaches require one complete search for each deployment…
Convolutional neural networks (CNNs) are the backbones of deep learning paradigms for numerous vision tasks. Early advancements in CNN architectures are primarily driven by human expertise and by e…