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{{Short description|Machine learning-powered structure design}}
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'''Neural architecture search''' ('''NAS''')<ref name="survey">{{Cite journal|url=http://jmlr.org/papers/v20/18-598.html|title=Neural Architecture Search: A Survey|first1=Thomas|last1=Elsken|first2=Jan Hendrik|last2=Metzen|first3=Frank|last3=Hutter|date=August 8, 2019|journal=Journal of Machine Learning Research|volume=20|issue=55|pages=1–21|via=jmlr.org|bibcode=2018arXiv180805377E|arxiv=1808.05377}}</ref><ref name="survey2">{{cite arXiv|last1=Wistuba|first1=Martin|last2=Rawat|first2=Ambrish|last3=Pedapati|first3=Tejaswini|date=2019-05-04|title=A Survey on Neural Architecture Search|eprint=1905.01392|class=cs.LG}}</ref> is a technique for automating the design of [[artificial neural network]]s (ANN), a widely used model in the field of [[machine learning]]. NAS has been used to design networks that are on par or outperform hand-designed architectures.<ref name="Zoph 2016" /><ref name="Zoph 2017">{{cite arXiv|last1=Zoph|first1=Barret|last2=Vasudevan|first2=Vijay|last3=Shlens|first3=Jonathon|last4=Le|first4=Quoc V.|date=2017-07-21|title=Learning Transferable Architectures for Scalable Image Recognition|eprint=1707.07012|class=cs.CV}}</ref> Methods for NAS can be categorized according to the search space, search strategy and performance estimation strategy used:<ref name="survey" />
 
* The ''search space'' defines the type(s) of ANN that can be designed and optimized.
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* {{cite arXiv |eprint=1905.01392 |class=cs.LG |first1=Martin |last1=Wistuba |first2=Ambrish |last2=Rawat |title=A Survey on Neural Architecture Search |date=2019-05-04 |last3=Pedapati |first3=Tejaswini}}
* {{Cite journal |last1=Elsken |first1=Thomas |last2=Metzen |first2=Jan Hendrik |last3=Hutter |first3=Frank |date=August 8, 2019 |title=Neural Architecture Search: A Survey |url=http://jmlr.org/papers/v20/18-598.html |journal=Journal of Machine Learning Research |volume=20 |issue=55 |pages=1–21 |arxiv=1808.05377 |bibcode=2018arXiv180805377E |via=jmlr.org}}
* {{cite journal |last1=Liu |first1=Yuqiao |last2=Sun |first2=Yanan |last3=Xue |first3=Bing |last4=Zhang |first4=Mengjie |last5=Yen |first5=Gary G |last6=Tan |first6=Kay Chen |year=2021 |title=A Survey on Evolutionary Neural Architecture Search |journal=IEEE Transactions on Neural Networks and Learning Systems |volume=PP |issue=2 |pages=1–21 |arxiv=2008.10937 |doi=10.1109/TNNLS.2021.3100554 |pmid=34357870 |s2cid=221293236}}
* {{Citationcite arxiv |last1=White |first1=Colin |title=Neural Architecture Search: Insights from 1000 Papers |date=2023-01-25 |url=http://arxiv.org/abs/2301.08727 |access-date=2024-01-29 |arxiv=2301.08727 |last2=Safari |first2=Mahmoud |last3=Sukthanker |first3=Rhea |last4=Ru |first4=Binxin |last5=Elsken |first5=Thomas |last6=Zela |first6=Arber |last7=Dey |first7=Debadeepta |last8=Hutter |first8=Frank}}
 
==References==