{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,28]],"date-time":"2025-06-28T04:43:49Z","timestamp":1751085829507,"version":"3.37.3"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["DMS-1854434","DMS-1952644"],"award-info":[{"award-number":["DMS-1854434","DMS-1952644"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005144","name":"Qualcomm Faculty Award","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005144","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/access.2022.3185095","type":"journal-article","created":{"date-parts":[[2022,6,21]],"date-time":"2022-06-21T19:41:15Z","timestamp":1655840475000},"page":"65901-65912","source":"Crossref","is-referenced-by-count":5,"title":["RARTS: An Efficient First-Order Relaxed Architecture Search Method"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8366-9591","authenticated-orcid":false,"given":"Fanghui","family":"Xue","sequence":"first","affiliation":[{"name":"Department of Mathematics, University of California at Irvine, Irvine, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingyong","family":"Qi","sequence":"additional","affiliation":[{"name":"Department of Mathematics, University of California at Irvine, Irvine, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6438-8476","authenticated-orcid":false,"given":"Jack","family":"Xin","sequence":"additional","affiliation":[{"name":"Department of Mathematics, University of California at Irvine, Irvine, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Neural architecture search with reinforcement learning","author":"Zoph","year":"2016","journal-title":"arXiv:1611.01578"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00907"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00720"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00017"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-05318-5_3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3447582"},{"key":"ref7","article-title":"ProxylessNAS: Direct neural architecture search on target task and hardware","author":"Cai","year":"2018","journal-title":"arXiv:1812.00332"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_2"},{"key":"ref9","article-title":"Efficient neural architecture search via parameter sharing","author":"Pham","year":"2018","journal-title":"arXiv:1802.03268"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014780"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-46147-8_29"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01099"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58517-4_32"},{"key":"ref14","article-title":"Darts: Differentiable architecture search","author":"Liu","year":"2018","journal-title":"arXiv:1806.09055"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01201"},{"key":"ref16","article-title":"FasterSeg: Searching for faster real-time semantic segmentation","author":"Chen","year":"2019","journal-title":"arXiv:1912.10917"},{"article-title":"Learning multiple layers of features from tiny images","year":"2009","author":"Krizhevsky","key":"ref17"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00186"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58555-6_28"},{"key":"ref20","first-page":"760","article-title":"Network pruning via transformable architecture search","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Dong"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.298"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01270-0_19"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3105366"},{"key":"ref24","first-page":"2074","article-title":"Learning structured sparsity in deep neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wen"},{"key":"ref25","first-page":"1","article-title":"Attention is all you need","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Vaswani"},{"key":"ref26","article-title":"An image is worth $16\\times16$\n words: Transformers for image recognition at scale","author":"Dosovitskiy","year":"2020","journal-title":"arXiv:2010.11929"},{"key":"ref27","article-title":"SNAS: Stochastic neural architecture search","author":"Xie","year":"2018","journal-title":"arXiv:1812.09926"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3054824"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-007-0176-2"},{"key":"ref33","first-page":"1568","article-title":"Bilevel programming for hyperparameter optimization and meta-learning","volume-title":"Proc. ICML","author":"Franceschi"},{"key":"ref34","article-title":"Rethinking architecture selection in differentiable NAS","author":"Wang","year":"2021","journal-title":"arXiv:2108.04392"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00138"},{"key":"ref36","article-title":"PC-DARTS: Partial channel connections for memory-efficient architecture search","author":"Xu","year":"2019","journal-title":"arXiv:1907.05737"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_48"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00293"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01298"},{"key":"ref40","first-page":"367","article-title":"Random search and reproducibility for neural architecture search","volume-title":"Proc. Uncertainty Artif. Intell.","author":"Li"},{"key":"ref41","article-title":"Network trimming: A data-driven neuron pruning approach towards efficient deep architectures","author":"Hu","year":"2016","journal-title":"arXiv:1607.03250"},{"key":"ref42","article-title":"Pruning filters for efficient ConvNets","author":"Li","year":"2016","journal-title":"arXiv:1608.08710"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.155"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.541"},{"key":"ref45","article-title":"Rethinking the value of network pruning","author":"Liu","year":"2018","journal-title":"arXiv:1810.05270"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2005.00532.x"},{"key":"ref47","article-title":"Rethinking the smaller-norm-less-informative assumption in channel pruning of convolution layers","author":"Ye","year":"2018","journal-title":"arXiv:1802.00124"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00339"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-55180-3_27"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.56021\/9781421407944"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1503.02531"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/6287639\/9668973\/9802086-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9668973\/09802086.pdf?arnumber=9802086","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T04:42:39Z","timestamp":1706762559000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9802086\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":52,"URL":"https:\/\/doi.org\/10.1109\/access.2022.3185095","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2022]]}}}