Abstract Deep Neural Networks have received considerable attention in recent years. As the
complexity of network architecture increases in relation to the task complexity, it becomes …

Neural Architecture Search (NAS) has received increasing attention because of its
exceptional merits in automating the design of Deep Neural Network (DNN) architectures …

Neural Architecture Search (NAS) aims to automatically find effective architectures within a
predefined search space. However, the search space is often extremely large. As a result …

Neural Architecture Search (NAS) has received increasing attention because of its
exceptional merits in automating the design of Deep Neural Network (DNN) architectures …

This survey focuses on categorizing and evaluating the methods of supernet optimization in
the field of Neural Architecture Search (NAS). Supernet optimization involves training a …

Neural predictors have shown great potential in the evaluation process of neural
architecture search (NAS). However, current predictor-based approaches overlook the fact …

Computational resources represent a significant bottleneck across all current deep learning
computer vision approaches. Image and video data storage requirements for training deep …