{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,17]],"date-time":"2025-01-17T08:40:17Z","timestamp":1737103217739,"version":"3.33.0"},"reference-count":19,"publisher":"IEEE","license":[{"start":{"date-parts":[[2024,12,15]],"date-time":"2024-12-15T00:00:00Z","timestamp":1734220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,12,15]],"date-time":"2024-12-15T00:00:00Z","timestamp":1734220800000},"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":[],"published-print":{"date-parts":[[2024,12,15]]},"DOI":"10.1109\/bigdata62323.2024.10825611","type":"proceedings-article","created":{"date-parts":[[2025,1,16]],"date-time":"2025-01-16T18:31:23Z","timestamp":1737052283000},"page":"8062-8069","source":"Crossref","is-referenced-by-count":0,"title":["DHFM-FLM: A Dynamic Hierarchical Federated Learning Mechanism for Financial Models under Client Resource Heterogeneity"],"prefix":"10.1109","author":[{"given":"Kangning","family":"Yin","sequence":"first","affiliation":[{"name":"University of Electronic Science and Technology of China,Kash Institute of Electronics and Information Industry,Chengdu,China"}]},{"given":"Zhen","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Information Management Wuhan University Big Data Research Institute Wuhan University,Wuhan,China"}]},{"given":"Shaoqi","family":"Hou","sequence":"additional","affiliation":[{"name":"Shanghai New Energy Vehicle Public Data Collection and Monitoring Research Center,Shanghai,China"}]},{"given":"Xinhui","family":"Ji","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China,School of Information and Software Engineering,Chengdu,China"}]},{"given":"Guangqiang","family":"Yin","sequence":"additional","affiliation":[{"name":"Shanghai New Energy Vehicle Public Data Collection and Monitoring Research Center,Shanghai,China"}]},{"given":"Zhiguo","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai New Energy Vehicle Public Data Collection and Monitoring Research Center,Shanghai,China"}]}],"member":"263","reference":[{"issue":"1","key":"ref1","first-page":"139","article-title":"STATUS, SHORTAGE AND SUGGESTIONS OF FINANCIAL DATA FACTOR MANAGEMENT IN CHINA","volume":"8","author":"Haoming","year":"2023","journal-title":"Journal of Business Innovation"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1080\/1097198X.2019.1569186"},{"key":"ref3","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"in Artificial intelligence and statistics","author":"McMahan","year":"2017"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1109\/COMST.2021.3075439"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1016\/j.cosrev.2023.100595"},{"year":"2024","article-title":"All Lending Club loan data","key":"ref6"},{"year":"2024","article-title":"Vehicle Insurance Claim Fraud Detection","key":"ref7"},{"year":"2024","article-title":"Taiwanese Bankruptcy Prediction","key":"ref8"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.1109\/MIS.2021.3114610"},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1609\/aaai.v36i4.20345"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1016\/j.dt.2024.08.015"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1609\/aaai.v35i9.16920"},{"key":"ref13","first-page":"23034","article-title":"ProgFed: Effective, communication, and computation efficient federated learning by progressive training","volume-title":"International Conference on Machine Learning","author":"Wang"},{"doi-asserted-by":"publisher","key":"ref14","DOI":"10.1609\/aaai.v36i8.20853"},{"key":"ref15","first-page":"4587","article-title":"Dispfl: Towards communication-efficient personalized federated learning via decentralized sparse training","volume-title":"International conference on machine learning","author":"Dai"},{"key":"ref16","first-page":"25501","article-title":"QSFL: A two-level uplink communication optimization framework for federated learning","volume-title":"International Conference on Machine Learning","author":"Yi"},{"issue":"100","key":"ref17","first-page":"1","article-title":"Fedlab: A flexible federated learning framework","volume":"24","author":"Zeng","year":"2023","journal-title":"Journal of Machine Learning Research"},{"year":"2019","author":"Li","article-title":"Fair resource allocation in federated learning","key":"ref18"},{"year":"2019","author":"Xie","article-title":"Asynchronous federated optimization","key":"ref19"}],"event":{"name":"2024 IEEE International Conference on Big Data (BigData)","start":{"date-parts":[[2024,12,15]]},"location":"Washington, DC, USA","end":{"date-parts":[[2024,12,18]]}},"container-title":["2024 IEEE International Conference on Big Data (BigData)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10824975\/10824942\/10825611.pdf?arnumber=10825611","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,17]],"date-time":"2025-01-17T08:03:58Z","timestamp":1737101038000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10825611\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,15]]},"references-count":19,"URL":"https:\/\/doi.org\/10.1109\/bigdata62323.2024.10825611","relation":{},"subject":[],"published":{"date-parts":[[2024,12,15]]}}}