{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:17:49Z","timestamp":1774628269937,"version":"3.50.1"},"reference-count":54,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"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":["2022YFB3304600"],"award-info":[{"award-number":["2022YFB3304600"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2020M680924"],"award-info":[{"award-number":["2020M680924"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Basic Research Projects of Liaoning Provincial Department of Education","award":["LJKMZ20220368"],"award-info":[{"award-number":["LJKMZ20220368"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Syst. Man Cybern, Syst."],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1109\/tsmc.2024.3453549","type":"journal-article","created":{"date-parts":[[2024,9,26]],"date-time":"2024-09-26T17:48:25Z","timestamp":1727372905000},"page":"7434-7444","source":"Crossref","is-referenced-by-count":2,"title":["A Group Regularization Framework of Convolutional Neural Networks Based on the Impact of <i>L\u209a<\/i> Regularizers on Magnitude"],"prefix":"10.1109","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7785-6013","authenticated-orcid":false,"given":"Feng","family":"Li","sequence":"first","affiliation":[{"name":"School of Science, Dalian Maritime University, Dalian, China"}]},{"given":"Yaokai","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Science, Dalian Maritime University, Dalian, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7394-7295","authenticated-orcid":false,"given":"Huisheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Science, Dalian Maritime University, Dalian, China"}]},{"given":"Ansheng","family":"Deng","sequence":"additional","affiliation":[{"name":"Information Science and Technology College, Dalian Maritime University, Dalian, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6622-534X","authenticated-orcid":false,"given":"Jacek M.","family":"Zurada","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-022-10210-8"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2022.3192017"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2023.3340710"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2023.3257416"},{"key":"ref5","first-page":"2270","article-title":"Learning the number of neurons in deep networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Alvarez"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2020.2972695"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i11.17180"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108257"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.l803.03635"},{"key":"ref10","first-page":"129","article-title":"What is the state of neural network pruning?","volume-title":"Proc. Mach. Learn. Syst.","volume":"2","author":"Blalock"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2950105"},{"key":"ref12","first-page":"598","article-title":"Optimal brain damage","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"LeCun"},{"key":"ref13","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Han"},{"key":"ref14","first-page":"1","article-title":"Pruning filters for efficient convnets","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Li"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.155"},{"key":"ref16","first-page":"2074","article-title":"Learning structured sparsity in deep neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wen"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.06.046"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2893266"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.12.014"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2020.3043584"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2023.3304850"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-010-0090-0"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2014.2309076"},{"key":"ref25","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.109206","article-title":"Training compact DNNs with \u21131\/2 regularization","volume":"136","author":"Tang","year":"2023","journal-title":"Pattern Recogn."},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2005.00532.x"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2864142"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2980383"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2019.2930616"},{"key":"ref30","first-page":"988","article-title":"Exclusive lasso for multi-task feature selection","volume-title":"Proc. 13th Int. Conf. Artif. Intell. Stat.","author":"Zhou"},{"key":"ref31","first-page":"1655","article-title":"Exclusive feature learning on arbitrary structures via \u21131,2-norm","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Kong"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2012.681250"},{"key":"ref33","first-page":"3958","article-title":"Combined group and exclusive sparsity for deep neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yoon"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.08.015"},{"key":"ref35","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Han"},{"key":"ref36","first-page":"3180","article-title":"Net-Trim: Convex pruning of deep neural networks with performance guarantee","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Aghasi"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1137\/19M1246468"},{"key":"ref38","article-title":"Training compressed fully-connected networks with a density-diversity penalty","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Wang"},{"key":"ref39","first-page":"1","article-title":"Pruning convolutional neural networks for resource efficient inference","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Molchanov"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3005348"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/309"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2019.2961233"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.02.029"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.3389\/fams.2020.529564"},{"key":"ref45","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":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2013.11.006"},{"key":"ref48","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arxiv:1412.6980"},{"issue":"229","key":"ref49","first-page":"1","article-title":"Towards practical Adam: Nonconvexity, convergence theory, and mini-batch acceleration","volume":"23","author":"Chen","year":"2022","journal-title":"J. Mach. Learn. Res."},{"key":"ref50","first-page":"28386","article-title":"Adam can converge without any modification on update rules","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhang"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref53","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014","journal-title":"arXiv:1409.1556"},{"key":"ref54","first-page":"1457","article-title":"Non-negative matrix factorization with sparseness constraints","volume":"5","author":"Hoyer","year":"2004","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Systems, Man, and Cybernetics: Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6221021\/10758325\/10695098.pdf?arnumber=10695098","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:34:42Z","timestamp":1732667682000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10695098\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12]]},"references-count":54,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tsmc.2024.3453549","relation":{},"ISSN":["2168-2216","2168-2232"],"issn-type":[{"value":"2168-2216","type":"print"},{"value":"2168-2232","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12]]}}}