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

• Published in: Knowledge-based systems Vol. 212; p. 106622
• Main Authors: He, Xin, Zhao, Kaiyong, Chu, Xiaowen
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 05.01.2021; Elsevier Science Ltd
• Subjects: Algorithms; Automated machine learning (autoML); Deep learning; Hyperparameter optimization (HPO); Machine learning; Neural architecture search (NAS); Object recognition; Optimization; State-of-the-art reviews; Deep learning; Neural architecture search (NAS); Automated machine learning (autoML); Hyperparameter optimization (HPO)

Deep learning (DL) techniques have obtained remarkable achievements on various tasks, such as image recognition, object detection, and language modeling. However, building a high-quality DL system for a specific task highly relies on human expertise, hindering its wide application. Meanwhile, automa...