{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T04:52:31Z","timestamp":1780635151895,"version":"3.54.1"},"reference-count":35,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Signal Process. Lett."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/lsp.2025.3577924","type":"journal-article","created":{"date-parts":[[2025,6,6]],"date-time":"2025-06-06T13:45:18Z","timestamp":1749217518000},"page":"2504-2508","source":"Crossref","is-referenced-by-count":3,"title":["A Novel Pruning Algorithm Based on Data-Driven and Knowledge-Driven Global Channel Pruning"],"prefix":"10.1109","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6566-775X","authenticated-orcid":false,"given":"Wei","family":"Lu","sequence":"first","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3182-3754","authenticated-orcid":false,"given":"Xinjie","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Future Technology, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2502-4936","authenticated-orcid":false,"given":"Yang","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7926-8824","authenticated-orcid":false,"given":"Jinghui","family":"Chu","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Simonyan","year":"2015"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref3","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Han","year":"2015"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3349004"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3015992"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3102504"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2874634"},{"key":"ref8","article-title":"Bit-pruning: A sparse multiplication-less dot-product","volume-title":"Proc. 11th Int. Conf. Learn. Representations","author":"Sekikawa","year":"2023"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3179616"},{"key":"ref10","first-page":"4475","article-title":"Optimal brain compression: A framework for accurate post-training quantization and pruning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Frantar","year":"2022"},{"key":"ref11","first-page":"20415","article-title":"Position-based scaled gradient for model quantization and pruning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Kim","year":"2020"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2021.3101670"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01465"},{"key":"ref14","first-page":"12557","article-title":"iDARTS: Differentiable architecture search with stochastic implicit gradients","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zhang","year":"2021"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/449"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11060945"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.643"},{"key":"ref18","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Han","year":"2015"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3334614"},{"key":"ref20","article-title":"Pruning filters for efficient convnets","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Li","year":"2017"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00447"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00290"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00160"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00289"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3031031"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICME52920.2022.9859866"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2023.11.065"},{"key":"ref28","article-title":"Trainability preserving neural pruning","volume-title":"Proc. 11th Int. Conf. Learn. Representations","author":"Wang","year":"2023"},{"key":"ref29","first-page":"25656","article-title":"Topology-aware network pruning using multi-stage graph embedding and reinforcement learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yu","year":"2022"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10094874"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00142"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3260903"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3416316"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICME55011.2023.00248"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6910"}],"container-title":["IEEE Signal Processing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/97\/10802935\/11027774.pdf?arnumber=11027774","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,5]],"date-time":"2025-08-05T04:38:39Z","timestamp":1754368719000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11027774\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/lsp.2025.3577924","relation":{},"ISSN":["1070-9908","1558-2361"],"issn-type":[{"value":"1070-9908","type":"print"},{"value":"1558-2361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}