{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T22:35:59Z","timestamp":1740177359249,"version":"3.37.3"},"reference-count":32,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61925305","61890930-3"],"award-info":[{"award-number":["61925305","61890930-3"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Basic Science Center Program","doi-asserted-by":"publisher","award":["61988101"],"award-info":[{"award-number":["61988101"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"International (Regional) Cooperation and Exchange Project","award":["61720106008"],"award-info":[{"award-number":["61720106008"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cogn. Dev. Syst."],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1109\/tcds.2020.3017100","type":"journal-article","created":{"date-parts":[[2020,8,17]],"date-time":"2020-08-17T21:57:33Z","timestamp":1597701453000},"page":"102-115","source":"Crossref","is-referenced-by-count":3,"title":["Accurate and Fast Deep Evolutionary Networks Structured Representation Through Activating and Freezing Dense Networks"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6162-1730","authenticated-orcid":false,"given":"Dayu","family":"Tan","sequence":"first","affiliation":[{"name":"Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4285-4739","authenticated-orcid":false,"given":"Weimin","family":"Zhong","sequence":"additional","affiliation":[{"name":"Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9277-8415","authenticated-orcid":false,"given":"Xin","family":"Peng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6509-2549","authenticated-orcid":false,"given":"Qiang","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8342-9707","authenticated-orcid":false,"given":"Vladimir","family":"Mahalec","sequence":"additional","affiliation":[{"name":"Department of Chemical Engineering, School of Engineering Practice and Technology, McMaster University, Hamilton, Canada"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.5555\/2999134.2999257"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298664"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.4324\/9781410605337-29"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"volume-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","year":"2015","author":"Ioffe","key":"ref6"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_39"},{"key":"ref8","first-page":"562","article-title":"Deeply-supervised nets","volume-title":"Proc. Int. Conf. Artif. Intell. Stat.","author":"Lee"},{"key":"ref9","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","volume-title":"Proc. 13th Int. Conf. Artif. Intell. Stat.","author":"Glorot"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.634"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.415"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2968521"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-038"},{"key":"ref16","first-page":"2377","article-title":"Training very deep networks","volume-title":"Proc. 28th Int. Conf. Adv. Neural Inf. Process. Syst.","author":"Srivastava"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2502579"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT.2012.6283927"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2873305"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01285"},{"key":"ref21","first-page":"1232","article-title":"Large scale distributed deep networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Dean"},{"volume-title":"Adaptive gradient methods with dynamic bound of learning rate","year":"2019","author":"Luo","key":"ref22"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.222"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/7503.003.0024"},{"volume-title":"Memory bounded deep convolutional networks","year":"2014","author":"Collins","key":"ref25"},{"key":"ref26","first-page":"103","article-title":"GPipe: Efficient training of Giant neural networks using pipeline parallelism","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Huang"},{"key":"ref27","first-page":"4467","article-title":"Dual path networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Chen"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00262"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"volume-title":"Network in network","year":"2013","author":"Lin","key":"ref30"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.7312\/haza92762-003"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.5244\/C.30.87"}],"container-title":["IEEE Transactions on Cognitive and Developmental Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7274989\/9732511\/09169711.pdf?arnumber=9169711","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T23:16:43Z","timestamp":1704842203000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9169711\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3]]},"references-count":32,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tcds.2020.3017100","relation":{},"ISSN":["2379-8920","2379-8939"],"issn-type":[{"type":"print","value":"2379-8920"},{"type":"electronic","value":"2379-8939"}],"subject":[],"published":{"date-parts":[[2022,3]]}}}