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Des. Autom. Electron. Syst."],"published-print":{"date-parts":[[2022,11,30]]},"abstract":"<jats:p>Layout hotspot detection is of great importance in the physical verification flow. Deep neural network models have been applied to hotspot detection and achieved great success. Despite their success, high-performance neural networks are still quite difficult to design. In this article, we propose a bayesian optimization-based neural architecture search scheme to automatically do this time-consuming and fiddly job. Experimental results on ICCAD 2012 and ICCAD 2019 Contest benchmarks show that the architectures designed by our proposed scheme achieve higher performance on hotspot detection task compared with state-of-the-art manually designed neural networks.<\/jats:p>","DOI":"10.1145\/3517130","type":"journal-article","created":{"date-parts":[[2022,2,18]],"date-time":"2022-02-18T19:50:50Z","timestamp":1645213850000},"page":"1-16","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["Efficient Layout Hotspot Detection via Neural Architecture Search"],"prefix":"10.1145","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9031-3179","authenticated-orcid":false,"given":"Yiyang","family":"Jiang","sequence":"first","affiliation":[{"name":"State Key Lab of AISC &amp; System, School of Microelectronics, Fudan University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2164-8175","authenticated-orcid":false,"given":"Fan","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Lab of AISC &amp; System, School of Microelectronics, Fudan University, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6406-4810","authenticated-orcid":false,"given":"Bei","family":"Yu","sequence":"additional","affiliation":[{"name":"Chinese University of Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2648-5232","authenticated-orcid":false,"given":"Dian","family":"Zhou","sequence":"additional","affiliation":[{"name":"University of Texas at Dallas"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8097-4053","authenticated-orcid":false,"given":"Xuan","family":"Zeng","sequence":"additional","affiliation":[{"name":"State Key Lab of AISC &amp; System, School of Microelectronics, Fudan University, China"}]}],"member":"320","published-online":{"date-parts":[[2022,6,27]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/3316781.3317824"},{"key":"e_1_3_1_3_2","doi-asserted-by":"crossref","unstructured":"Ying Chen Yibo Lin Tianyang Gai Yajuan Su Yayi Wei and David Z. 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