{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T17:56:31Z","timestamp":1778262991786,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":29,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,1,15]],"date-time":"2022-01-15T00:00:00Z","timestamp":1642204800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,1,15]]},"DOI":"10.1145\/3523150.3523166","type":"proceedings-article","created":{"date-parts":[[2022,4,13]],"date-time":"2022-04-13T21:39:55Z","timestamp":1649885995000},"page":"98-104","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["Personnel status detection model suitable for vertical federated learning structure"],"prefix":"10.1145","author":[{"given":"Jie","family":"Ji","sequence":"first","affiliation":[{"name":"Beijing University of Posts and Telecommunications, China"}]},{"given":"Danfeng","family":"Yan","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, China"}]},{"given":"Zhengyang","family":"Mu","sequence":"additional","affiliation":[{"name":"Beijing University of Posts and Telecommunications, China"}]}],"member":"320","published-online":{"date-parts":[[2022,4,13]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"QSGD: Communication-efficient SGD via gradient quantization and encoding. Advances in Neural Information Processing Systems 2017-Decem, 1","author":"Alistarh Dan","year":"2017","unstructured":"Dan Alistarh , Demjan Grubic , Jerry Z. Li , Ryota Tomioka , and Milan Vojnovic . 2017 . QSGD: Communication-efficient SGD via gradient quantization and encoding. Advances in Neural Information Processing Systems 2017-Decem, 1 (2017), 1710\u20131721. arXiv:1610.02132 Dan Alistarh, Demjan Grubic, Jerry Z. Li, Ryota Tomioka, and Milan Vojnovic. 2017. QSGD: Communication-efficient SGD via gradient quantization and encoding. Advances in Neural Information Processing Systems 2017-Decem, 1 (2017), 1710\u20131721. arXiv:1610.02132"},{"key":"e_1_3_2_1_2_1","unstructured":"R Bousseljot D Kreiseler and A Schnabel. 1995. Nutzung der EKG-Signaldatenbank CARDIODAT der PTB \u00fcber das Internet. (1995).  R Bousseljot D Kreiseler and A Schnabel. 1995. Nutzung der EKG-Signaldatenbank CARDIODAT der PTB \u00fcber das Internet. (1995)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2020.2988604"},{"issue":"4","key":"e_1_3_2_1_4_1","article-title":"SecureBoost: A Lossless Federated Learning Framework. IEEE Intelligent Systems (2021), 1\u20139. https:\/\/doi.org\/10.1109\/MIS.2021","volume":"37","author":"Cheng Kewei","year":"2021","unstructured":"Kewei Cheng , Tao Fan , Yilun Jin , Yang Liu , Tianjian Chen , Dimitrios Papadopoulos , and Qiang Yang . 2021 . SecureBoost: A Lossless Federated Learning Framework. IEEE Intelligent Systems (2021), 1\u20139. https:\/\/doi.org\/10.1109\/MIS.2021 . J. ACM , Vol. 37 , No. 4 , Article 111. Publication date: August 2018. 3082561 arXiv:1901.08755 10.1109\/MIS.2021 Kewei Cheng, Tao Fan, Yilun Jin, Yang Liu, Tianjian Chen, Dimitrios Papadopoulos, and Qiang Yang. 2021. SecureBoost: A Lossless Federated Learning Framework. IEEE Intelligent Systems (2021), 1\u20139. https:\/\/doi.org\/10.1109\/MIS.2021. J. ACM, Vol. 37, No. 4, Article 111. Publication date: August 2018. 3082561 arXiv:1901.08755","journal-title":"J. ACM"},{"key":"e_1_3_2_1_5_1","first-page":"1","article-title":"Characterisation of mental health conditions in social media using Informed Deep Learning","volume":"7","author":"Gkotsis George","year":"2017","unstructured":"George Gkotsis , Anika Oellrich , Sumithra Velupillai , Maria Liakata , Tim J.P. Hubbard , Richard J.B. Dobson , and Rina Dutta . 2017 . Characterisation of mental health conditions in social media using Informed Deep Learning . Scientific Reports 7 (2017), 1 \u2013 11 . https:\/\/doi.org\/10.1038\/srep45141 10.1038\/srep45141 George Gkotsis, Anika Oellrich, Sumithra Velupillai, Maria Liakata, Tim J.P. Hubbard, Richard J.B. Dobson, and Rina Dutta. 2017. Characterisation of mental health conditions in social media using Informed Deep Learning. Scientific Reports 7 (2017), 1\u201311. https:\/\/doi.org\/10.1038\/srep45141","journal-title":"Scientific Reports"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2582924"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00165"},{"key":"e_1_3_2_1_8_1","unstructured":"Andrew Hard Kanishka Rao Rajiv Mathews Swaroop Ramaswamy Fran\u00e7oise Beaufays Sean Augenstein Hubert Eichner Chlo\u00e9 Kiddon and Daniel Ramage. 2018. Federated Learning for Mobile Keyboard Prediction. (2018). arXiv:1811.03604 http:\/\/arxiv.org\/abs\/1811.03604  Andrew Hard Kanishka Rao Rajiv Mathews Swaroop Ramaswamy Fran\u00e7oise Beaufays Sean Augenstein Hubert Eichner Chlo\u00e9 Kiddon and Daniel Ramage. 2018. Federated Learning for Mobile Keyboard Prediction. (2018). arXiv:1811.03604 http:\/\/arxiv.org\/abs\/1811.03604"},{"key":"e_1_3_2_1_9_1","unstructured":"Stephen Hardy Wilko Henecka Hamish Ivey-Law Richard Nock Giorgio Patrini Guillaume Smith and Brian Thorne. 2017. Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption. (2017). arXiv:1711.10677 http:\/\/arxiv.org\/abs\/1711.10677  Stephen Hardy Wilko Henecka Hamish Ivey-Law Richard Nock Giorgio Patrini Guillaume Smith and Brian Thorne. 2017. Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption. (2017). arXiv:1711.10677 http:\/\/arxiv.org\/abs\/1711.10677"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.27480"},{"key":"e_1_3_2_1_11_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2015. Deep Residual Learning for Image Recognition. (2015). http:\/\/arxiv.org\/abs\/1512.03385  Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2015. Deep Residual Learning for Image Recognition. (2015). http:\/\/arxiv.org\/abs\/1512.03385"},{"key":"e_1_3_2_1_12_1","unstructured":"Irjet Journal. [n. d.]. IRJET- Credit Risk Assessment from Combined Bank Records using Federated Learning. ([n. d.]).  Irjet Journal. [n. d.]. IRJET- Credit Risk Assessment from Combined Bank Records using Federated Learning. ([n. d.])."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1561\/2200000083"},{"key":"e_1_3_2_1_14_1","volume-title":"Chi Hyuck Jun, and Xiaoqian Jiang","author":"Lee Junghye","year":"2018","unstructured":"Junghye Lee , Jimeng Sun , Fei Wang , Shuang Wang , Chi Hyuck Jun, and Xiaoqian Jiang . 2018 . Privacy-preserving patient similarity learning in a federated environment: Development and analysis. JMIR Medical Informatics 20, 4 (2018). https:\/\/doi.org\/10.2196\/medinform.7744 10.2196\/medinform.7744 Junghye Lee, Jimeng Sun, Fei Wang, Shuang Wang, Chi Hyuck Jun, and Xiaoqian Jiang. 2018. Privacy-preserving patient similarity learning in a federated environment: Development and analysis. JMIR Medical Informatics 20, 4 (2018). https:\/\/doi.org\/10.2196\/medinform.7744"},{"key":"#cr-split#-e_1_3_2_1_15_1.1","doi-asserted-by":"crossref","unstructured":"Dianbo Liu Dmitriy Dligach and Timothy Miller. 2019. Two-stage Federated Phenotyping and Patient Representation Learning. (2019) 283-291. https:\/\/doi.org\/10.18653\/v1\/w19-5030 arXiv:1908.05596 10.18653\/v1","DOI":"10.18653\/v1\/W19-5030"},{"key":"#cr-split#-e_1_3_2_1_15_1.2","doi-asserted-by":"crossref","unstructured":"Dianbo Liu Dmitriy Dligach and Timothy Miller. 2019. Two-stage Federated Phenotyping and Patient Representation Learning. (2019) 283-291. https:\/\/doi.org\/10.18653\/v1\/w19-5030 arXiv:1908.05596","DOI":"10.18653\/v1\/W19-5030"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i08.7021"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-63076-8_1"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2011.09.037"},{"key":"e_1_3_2_1_19_1","unstructured":"Radiological Society of North America. 2019. RSNA-ICH-Det. Retrieved October 2 2021 from https:\/\/www.kaggle. com\/c\/rsna-intracranial-hemorrhage-detection\/data  Radiological Society of North America. 2019. RSNA-ICH-Det. Retrieved October 2 2021 from https:\/\/www.kaggle. com\/c\/rsna-intracranial-hemorrhage-detection\/data"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-018-3689-5"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2985617"},{"key":"e_1_3_2_1_22_1","unstructured":"Pulkit Sharma Farah E Shamout and David A Clifton. 2019. Preserving Patient Privacy while Training a Predictive Model of In-hospital Mortality. (2019). arXiv:1912.00354 http:\/\/arxiv.org\/abs\/1912.00354  Pulkit Sharma Farah E Shamout and David A Clifton. 2019. Preserving Patient Privacy while Training a Predictive Model of In-hospital Mortality. (2019). arXiv:1912.00354 http:\/\/arxiv.org\/abs\/1912.00354"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2016.2579198"},{"key":"e_1_3_2_1_24_1","volume-title":"FATE: An industrial grade federated learning framework. Retrieved","year":"2019","unstructured":"WeBank. 2019 . FATE: An industrial grade federated learning framework. Retrieved October 2, 2021 from https:\/\/fate.fedai.org WeBank. 2019. FATE: An industrial grade federated learning framework. Retrieved October 2, 2021 from https:\/\/fate.fedai.org"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2017.09.005"},{"key":"e_1_3_2_1_26_1","volume-title":"A Federated Learning Framework for Healthcare IoT devices. 1","author":"Yuan Binhang","year":"2020","unstructured":"Binhang Yuan , Song Ge , and Wenhui Xing . 2020. A Federated Learning Framework for Healthcare IoT devices. 1 ( 2020 ). arXiv:2005.05083 http:\/\/arxiv.org\/abs\/2005.05083 Binhang Yuan, Song Ge, and Wenhui Xing. 2020. A Federated Learning Framework for Healthcare IoT devices. 1 (2020). arXiv:2005.05083 http:\/\/arxiv.org\/abs\/2005.05083"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2020.02.045"},{"key":"e_1_3_2_1_28_1","volume-title":"Guest Editorial: Federated Learning for Industrial IoT in Industry 4.0","author":"Zhou Jiehan","year":"2021","unstructured":"Jiehan Zhou , Qinghua Lu , Wenbin Dai , and Enrique Herrera-Viedma . 2021 . Guest Editorial: Federated Learning for Industrial IoT in Industry 4.0 . IEEE Transactions on Industrial Informatics 17, 12 (2021), 8438\u20138441. https: \/\/doi.org\/10.1109\/tii.2021.3086509 10.1109\/tii.2021.3086509 Jiehan Zhou, Qinghua Lu, Wenbin Dai, and Enrique Herrera-Viedma. 2021. Guest Editorial: Federated Learning for Industrial IoT in Industry 4.0. IEEE Transactions on Industrial Informatics 17, 12 (2021), 8438\u20138441. https: \/\/doi.org\/10.1109\/tii.2021.3086509"}],"event":{"name":"ICMLSC 2022: 2022 The 6th International Conference on Machine Learning and Soft Computing","location":"Haikou China","acronym":"ICMLSC 2022"},"container-title":["2022 The 6th International Conference on Machine Learning and Soft Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3523150.3523166","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3523150.3523166","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:44Z","timestamp":1750188644000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3523150.3523166"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,15]]},"references-count":29,"alternative-id":["10.1145\/3523150.3523166","10.1145\/3523150"],"URL":"https:\/\/doi.org\/10.1145\/3523150.3523166","relation":{},"subject":[],"published":{"date-parts":[[2022,1,15]]},"assertion":[{"value":"2022-04-13","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}