{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:00:09Z","timestamp":1774627209272,"version":"3.50.1"},"reference-count":68,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018AAA0100203"],"award-info":[{"award-number":["2018AAA0100203"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61973330"],"award-info":[{"award-number":["61973330"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62073085"],"award-info":[{"award-number":["62073085"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62350055"],"award-info":[{"award-number":["62350055"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Science and Technology Program","award":["JCYJ20230807093513027"],"award-info":[{"award-number":["JCYJ20230807093513027"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["1243300008"],"award-info":[{"award-number":["1243300008"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002726","name":"Beijing Normal University Tang Scholar","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002726","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1109\/tnnls.2025.3575505","type":"journal-article","created":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T13:41:10Z","timestamp":1750167670000},"page":"19356-19369","source":"Crossref","is-referenced-by-count":2,"title":["FX-DARTS: Designing Topology-Unconstrained Architectures With Differentiable Architecture Search and Entropy-BasedSuper-Network Shrinking"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-3142-3091","authenticated-orcid":false,"given":"Xuan","family":"Rao","sequence":"first","affiliation":[{"name":"School of Systems Science, Beijing Normal University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7684-7342","authenticated-orcid":false,"given":"Bo","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Systems Science, Beijing Normal University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3715-4778","authenticated-orcid":false,"given":"Derong","family":"Liu","sequence":"additional","affiliation":[{"name":"School of System Design and Intelligent Manufacturing, Southern University of Science and Technology, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3819-0025","authenticated-orcid":false,"given":"Cesare","family":"Alippi","sequence":"additional","affiliation":[{"name":"Dipartimento di Elettronica e Informazione, Politecnico di Milano, Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.4324\/9781410605337-29"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3095357"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2979670"},{"key":"ref5","article-title":"Optimal control via neural networks: A convex approach","author":"Chen","year":"2018","journal-title":"arXiv:1805.11835"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2805379"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2985720"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2018.2822828"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3136866"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-020-3071-8"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2006.875987"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2522428"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.195"},{"key":"ref15","first-page":"1","article-title":"Multi-scale context aggregation by dilated convolutions","volume-title":"Proc. 4th Int. Conf. Learn. Represent.","author":"Yu"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106622"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01044"},{"key":"ref18","first-page":"1","article-title":"DARTS: Differentiable architecture search","volume-title":"Proc. 7th Int. Conf. Learn. Represent.","author":"Liu"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00907"},{"key":"ref20","first-page":"1","article-title":"Designing neural network architectures using reinforcement learning","volume-title":"Proc. 5th Int. Conf. Learn. Represent.","author":"Baker"},{"key":"ref21","first-page":"4092","article-title":"Efficient neural srchitecture search via parameter sharing","volume-title":"Proc. 35th Int. Conf. Mach. Learn.","author":"Pham"},{"key":"ref22","first-page":"1","article-title":"Hierarchical representations for efficient architecture search","volume-title":"Proc. 6th Int. Conf. Learn. Represent.","author":"Liu"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014780"},{"key":"ref24","first-page":"7827","article-title":"Neural architecture optimization","volume-title":"Proc. Adv. Neural Inf. Process. Syst. (NIPS)","author":"Luo"},{"key":"ref25","first-page":"12486","article-title":"Does unsupervised architecture representation learning help neural architecture search?","volume-title":"Proc. 34th Int. Conf. Neural Inf. Process. Syst.","author":"Shen"},{"key":"ref26","first-page":"1586","article-title":"D-VAE: A variational autoencoder for directed acyclic graphs","volume-title":"Proc. 33rd Int. Conf. Neural Inf. Process. Syst.","author":"Zhang"},{"key":"ref27","article-title":"CR-LSO: Convex neural architecture optimization in the latent space of graph variational autoencoder with input convex neural networks","author":"Rao","year":"2022","journal-title":"arXiv:2211.05950"},{"key":"ref28","first-page":"1","article-title":"SNAS: Stochastic neural architecture search","volume-title":"Proc. 7th Int. Conf. Learn. Represent.","author":"Xie"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01396-x"},{"key":"ref30","article-title":"GOLD-NAS: Gradual, one-level, differentiable","author":"Bi","year":"2020","journal-title":"arXiv:2007.03331"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108186"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2023.3346169"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2022.11.015"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2023.3301395"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3293885"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3072950"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58555-6_28"},{"key":"ref38","first-page":"1","article-title":"DARTS-: Robustly stepping out of performance collapse without indicators","volume-title":"Proc. 9th Int. Conf. Learn. Represent.","author":"Chu"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.5244\/c.35.434"},{"key":"ref40","first-page":"367","article-title":"Random search and reproducibility for neural architecture search","volume-title":"Proc. 35th Conf. Uncertainty Artif. Intell.","author":"Li"},{"key":"ref41","first-page":"1","article-title":"NAS evaluation is frustratingly hard","volume-title":"Proc. 8th Int. Conf. Learn. Represent.","author":"Yang"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-46147-8_29"},{"key":"ref43","first-page":"1","article-title":"ProxylessNAS: Direct neural architecture search on target task and hardware","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Cai"},{"key":"ref44","first-page":"9880","article-title":"K-shot NAS: Learnable weight-sharing for NAS with K-shot supernets","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Su"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00716"},{"key":"ref47","first-page":"1","article-title":"An image is worth 16\u00d716 words: Transformers for image recognition at scale","volume-title":"Proc. 9th Int. Conf. Learn. Represent.","author":"Dosovitskiy"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9412285"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01213"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.3022673"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00137"},{"key":"ref52","article-title":"DNAD: Differentiable neural architecture distillation","author":"Rao","year":"2022","journal-title":"arXiv:2504.20080"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3059510"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3096658"},{"key":"ref55","first-page":"1975","article-title":"XNAS: Neural architecture search with expert advice","volume-title":"Proc. 34th Int. Conf. Neural Inf. Process. Syst.","volume":"32","author":"Nayman"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01060"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3153065"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_8"},{"key":"ref59","article-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","author":"Howard","year":"2017","journal-title":"arXiv:1704.04861"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00186"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.111466"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/tii.2023.3348843"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/tetci.2024.3359046"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2024.101736"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i10.28993"},{"key":"ref67","first-page":"70983","article-title":"Operation-level early stopping for robustifying differentiable NAS","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"36","author":"Jiang"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2024.127522"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/5962385\/11195929\/11038947.pdf?arnumber=11038947","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T17:39:01Z","timestamp":1759945141000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11038947\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10]]},"references-count":68,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2025.3575505","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10]]}}}