A comprehensive survey of neural architecture search: Challenges and solutions

P Ren, Y **ao, X Chang, PY Huang, Z Li… - ACM Computing …, 2021‏ - dl.acm.org
Deep learning has made substantial breakthroughs in many fields due to its powerful
automatic representation capabilities. It has been proven that neural architecture design is …

Deep learning and medical image analysis for COVID-19 diagnosis and prediction

T Liu, E Siegel, D Shen - Annual review of biomedical …, 2022‏ - annualreviews.org
The coronavirus disease 2019 (COVID-19) pandemic has imposed dramatic challenges to
health-care organizations worldwide. To combat the global crisis, the use of thoracic …

AutoML: A survey of the state-of-the-art

X He, K Zhao, X Chu - Knowledge-based systems, 2021‏ - Elsevier
Deep learning (DL) techniques have obtained remarkable achievements on various tasks,
such as image recognition, object detection, and language modeling. However, building a …

Automated machine learning: past, present and future

M Baratchi, C Wang, S Limmer, JN van Rijn… - Artificial intelligence …, 2024‏ - Springer
Automated machine learning (AutoML) is a young research area aiming at making high-
performance machine learning techniques accessible to a broad set of users. This is …

Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation

C Liu, LC Chen, F Schroff, H Adam… - Proceedings of the …, 2019‏ - openaccess.thecvf.com
Abstract Recently, Neural Architecture Search (NAS) has successfully identified neural
network architectures that exceed human designed ones on large-scale image …

Neural architecture search: A survey

T Elsken, JH Metzen, F Hutter - Journal of Machine Learning Research, 2019‏ - jmlr.org
Deep Learning has enabled remarkable progress over the last years on a variety of tasks,
such as image recognition, speech recognition, and machine translation. One crucial aspect …

Darts: Differentiable architecture search

H Liu, K Simonyan, Y Yang - arxiv preprint arxiv:1806.09055, 2018‏ - arxiv.org
This paper addresses the scalability challenge of architecture search by formulating the task
in a differentiable manner. Unlike conventional approaches of applying evolution or …

Nas-unet: Neural architecture search for medical image segmentation

Y Weng, T Zhou, Y Li, X Qiu - IEEE access, 2019‏ - ieeexplore.ieee.org
Neural architecture search (NAS) has significant progress in improving the accuracy of
image classification. Recently, some works attempt to extend NAS to image segmentation …

From federated learning to federated neural architecture search: a survey

H Zhu, H Zhang, Y ** - Complex & Intelligent Systems, 2021‏ - Springer
Federated learning is a recently proposed distributed machine learning paradigm for privacy
preservation, which has found a wide range of applications where data privacy is of primary …

Neural architecture search survey: A computer vision perspective

JS Kang, JK Kang, JJ Kim, KW Jeon, HJ Chung… - Sensors, 2023‏ - mdpi.com
In recent years, deep learning (DL) has been widely studied using various methods across
the globe, especially with respect to training methods and network structures, proving highly …