{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T16:29:02Z","timestamp":1774024142817,"version":"3.50.1"},"reference-count":43,"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":[{"name":"National Key R&#x0026;D Program of China","award":["2022YFE0112600"],"award-info":[{"award-number":["2022YFE0112600"]}]},{"name":"National Key Research and Development Project","award":["2021YFB1714200"],"award-info":[{"award-number":["2021YFB1714200"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62293481"],"award-info":[{"award-number":["62293481"]}],"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":["62201505"],"award-info":[{"award-number":["62201505"]}],"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":["U23A20326"],"award-info":[{"award-number":["U23A20326"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"SUTD-ZJU IDEA","award":["SUTD-ZJU (VP) 202102"],"award-info":[{"award-number":["SUTD-ZJU (VP) 202102"]}]},{"DOI":"10.13039\/100022963","name":"Key Research and Development Program of Zhejiang Province","doi-asserted-by":"publisher","award":["2021C03037"],"award-info":[{"award-number":["2021C03037"]}],"id":[{"id":"10.13039\/100022963","id-type":"DOI","asserted-by":"publisher"}]},{"name":"ZJUCSE-Enflame Cloud and Edge Intelligence Joint Laboratory"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Mobile Comput."],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1109\/tmc.2024.3389779","type":"journal-article","created":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T20:09:02Z","timestamp":1714507742000},"page":"10938-10951","source":"Crossref","is-referenced-by-count":4,"title":["AccEPT: An Acceleration Scheme for Speeding up Edge Pipeline-Parallel Training"],"prefix":"10.1109","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9905-5823","authenticated-orcid":false,"given":"Yuhao","family":"Chen","sequence":"first","affiliation":[{"name":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4789-1645","authenticated-orcid":false,"given":"Yuxuan","family":"Yan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4747-9410","authenticated-orcid":false,"given":"Qianqian","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9542-7095","authenticated-orcid":false,"given":"Yuanchao","family":"Shu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1505-6766","authenticated-orcid":false,"given":"Shibo","family":"He","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9160-048X","authenticated-orcid":false,"given":"Zhiguo","family":"Shi","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3155-3145","authenticated-orcid":false,"given":"Jiming","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/Ucom59132.2023.10257591"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.4324\/9780203978948-13"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3560815"},{"issue":"8","key":"ref5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3472290","article-title":"A survey on deep learning for human activity recognition","volume":"54","author":"Gu","year":"2021","journal-title":"ACM Comput. Surv."},{"key":"ref6","article-title":"Federated optimization: Distributed machine learning for on-device intelligence","author":"Kone\u010dny","year":"2016"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.2013.6549279"},{"key":"ref8","article-title":"PipeDream: Fast and efficient pipeline parallel DNN training","author":"Harlap","year":"2018"},{"key":"ref9","article-title":"Split learning for collaborative deep learning in healthcare","author":"Poirot","year":"2019"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3272567"},{"key":"ref11","first-page":"103","article-title":"GPipe: Efficient training of giant neural networks using pipeline parallelism","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Huang"},{"key":"ref12","article-title":"Split learning for health: Distributed deep learning without sharing raw patient data","author":"Vepakomma","year":"2018"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00171"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3081333.3081336"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11601"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3093337.3037698"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/AVSS.2018.8639121"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2019.2947893"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3372224.3419194"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3384419.3430898"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/OJCOMS.2020.2994737"},{"key":"ref22","first-page":"7937","article-title":"Memory-efficient pipeline-parallel DNN training","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Narayanan"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00310"},{"key":"ref24","article-title":"Towards accurate binary convolutional neural network","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Lin"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.14778\/3415478.3415530"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00801"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_23"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.430"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00141"},{"key":"ref30","article-title":"Estimating or propagating gradients through stochastic neurons for conditional computation","author":"Bengio","year":"2013"},{"key":"ref31","first-page":"1737","article-title":"Deep learning with limited numerical precision","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Gupta"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3458864.3467882"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_48"},{"key":"ref34","article-title":"Pruning filters for efficient convnets","author":"Li","year":"2016"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01099"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01166"},{"key":"ref37","first-page":"10480","article-title":"BRP-NAS: Prediction-based NAS using GCNs","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Dudziak"},{"key":"ref38","first-page":"437","article-title":"A public domain dataset for human activity recognition using smartphones","volume-title":"Proc. Eur. Symp. Artif. Neural Netw.","author":"Anguita"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2020.2988604"},{"key":"ref40","first-page":"215","article-title":"An analysis of single-layer networks in unsupervised feature learning","volume-title":"Proc. 14th Int. Conf. Artif. Intell. Statist.","author":"Coates"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1177\/0032258x7905200314"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref43","article-title":"Learned step size quantization","author":"Esser","year":"2019"}],"container-title":["IEEE Transactions on Mobile Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7755\/10746253\/10516335.pdf?arnumber=10516335","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:11:36Z","timestamp":1732666296000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10516335\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12]]},"references-count":43,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tmc.2024.3389779","relation":{},"ISSN":["1536-1233","1558-0660","2161-9875"],"issn-type":[{"value":"1536-1233","type":"print"},{"value":"1558-0660","type":"electronic"},{"value":"2161-9875","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12]]}}}