{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T04:30:34Z","timestamp":1769142634156,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":26,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819557158","type":"print"},{"value":"9789819557165","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-95-5716-5_3","type":"book-chapter","created":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T13:06:46Z","timestamp":1769087206000},"page":"33-48","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Data Augmentation Based Federated Client Selection with\u00a0Bandit Approach"],"prefix":"10.1007","author":[{"given":"Duyu","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruixuan","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,23]]},"reference":[{"issue":"10","key":"3_CR1","doi-asserted-by":"crossref","first-page":"8441","DOI":"10.1109\/TWC.2022.3166386","volume":"21","author":"C Feng","year":"2022","unstructured":"Feng, C., Yang, H.H., Hu, D., Zhao, Z., Quek, T.Q.S., Min, G.: Mobility-aware cluster federated learning in hierarchical wireless networks. IEEE Trans. Wireless Commun. 21(10), 8441\u20138458 (2022)","journal-title":"IEEE Trans. Wireless Commun."},{"issue":"3","key":"3_CR2","doi-asserted-by":"crossref","first-page":"3062","DOI":"10.1109\/TNSM.2022.3172370","volume":"19","author":"A Hammoud","year":"2022","unstructured":"Hammoud, A., Otrok, H., Mourad, A., Dziong, Z.: On demand fog federations for horizontal federated learning in IoV. IEEE Trans. Netw. Serv. Manage. 19(3), 3062\u20133075 (2022)","journal-title":"IEEE Trans. Netw. Serv. Manage."},{"issue":"6","key":"3_CR3","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1109\/MWC.001.2100102","volume":"28","author":"DC Nguyen","year":"2021","unstructured":"Nguyen, D.C., et al.: Federated learning for industrial internet of things in future industries. IEEE Wirel. Commun. 28(6), 192\u2013199 (2021)","journal-title":"IEEE Wirel. Commun."},{"key":"3_CR4","first-page":"1","volume":"2023","author":"KD Reddy","year":"2023","unstructured":"Reddy, K.D., Gadekallu, T.R.: A comprehensive survey on federated learning techniques for healthcare informatics. Comput. Intell. Neurosci. 2023, 1\u201325 (2023)","journal-title":"Comput. Intell. Neurosci."},{"issue":"1","key":"3_CR5","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1109\/JSAC.2023.3322798","volume":"42","author":"Z Chen","year":"2024","unstructured":"Chen, Z., Ge, X.: An information geometry inference approach of fine-grained spatial distribution for connected and automated vehicles. IEEE J. Sel. Areas Commun. 42(1), 192\u2013206 (2024)","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"3_CR6","doi-asserted-by":"crossref","unstructured":"Tegin, B., Duman, T.M.: Federated learning over time-varying channels. In: IEEE Global Communications Conference, pp. 1\u201306 (2021)","DOI":"10.1109\/GLOBECOM46510.2021.9685486"},{"issue":"3","key":"3_CR7","doi-asserted-by":"crossref","first-page":"1927","DOI":"10.1109\/TWC.2021.3108197","volume":"21","author":"Z Zhao","year":"2022","unstructured":"Zhao, Z., et al.: Federated learning with Non-IID data in wireless networks. IEEE Trans. Wireless Commun. 21(3), 1927\u20131942 (2022)","journal-title":"IEEE Trans. Wireless Commun."},{"issue":"11","key":"3_CR8","doi-asserted-by":"crossref","first-page":"352","DOI":"10.3390\/fi15110352","volume":"15","author":"MM Alam","year":"2023","unstructured":"Alam, M.M., Alzahrani, A., Zhang, Y., Wang, X.: Latency-aware semi-synchronous client selection and model aggregation for wireless federated learning. Future Internet 15(11), 352 (2023)","journal-title":"Future Internet"},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"Jiang, Z., Xu, Y., Xu, H., Wang, Z., Qian, C.: Heterogeneity-aware federated learning with adaptive client selection and gradient compression. In: IEEE International Conference on Computer Communication (2023)","DOI":"10.1109\/INFOCOM53939.2023.10229029"},{"issue":"2","key":"3_CR10","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1109\/LNET.2024.3363620","volume":"6","author":"P Singhal","year":"2024","unstructured":"Singhal, P., Pandey, S.R., Popovski, P.: Greedy Shapley client selection for communication-efficient federated learning. IEEE Netw. Lett. 6(2), 134\u2013138 (2024)","journal-title":"IEEE Netw. Lett."},{"key":"3_CR11","doi-asserted-by":"crossref","unstructured":"Nagalapatti, L., Narayanam, R.: Game of gradients: mitigating irrelevant clients in federated learning. In: Proceedings of the AAAI Conference on Artificial Intelligence (2021)","DOI":"10.1609\/aaai.v35i10.17093"},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Gauthier, F., Gogineni, V.C., Werner, S., Huang, Y.-F., Kuh, A.: Asynchronous online federated learning with reduced communication requirements. IEEE Internet Things J. 10(23), 20:761\u201320:775 (2023)","DOI":"10.1109\/JIOT.2023.3314923"},{"key":"3_CR13","unstructured":"Li, T., Sahu, A.K., Zaheer, M., Sanjabi, M., Talwalkar, A., Smith, V.: Federated optimization in heterogeneous networks. In: Proceedings of the Third Conference on Machine Learning and Systems (2020)"},{"issue":"1","key":"3_CR14","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/s11390-023-2972-9","volume":"39","author":"Y-C Mao","year":"2024","unstructured":"Mao, Y.-C., Shen, L.-J., Wu, J., Ping, P., Wu, J.: Federated dynamic client selection for fairness guarantee in heterogeneous edge computing. J. Comput. Sci. Technol. 39(1), 139\u2013158 (2024)","journal-title":"J. Comput. Sci. Technol."},{"issue":"2","key":"3_CR15","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1109\/TPDS.2022.3217271","volume":"34","author":"R Saha","year":"2023","unstructured":"Saha, R., Misra, S., Chakraborty, A., Chatterjee, C., Deb, P.K.: Data-centric client selection for federated learning over distributed edge networks. IEEE Trans. Parallel Distrib. Syst. 34(2), 675\u2013686 (2023)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"3_CR16","unstructured":"Chen, Z., Li, J., Shen, C.: Personalized federated learning with attention-based client selection. arXiv preprint arXiv:2312.15148 (2023)"},{"issue":"20","key":"3_CR17","doi-asserted-by":"crossref","first-page":"3229","DOI":"10.3390\/math12203229","volume":"12","author":"S Song","year":"2024","unstructured":"Song, S., Li, Y., Wan, J., Fu, X., Jiang, J.: Data quality-aware client selection in heterogeneous federated learning. Mathematics 12(20), 3229 (2024)","journal-title":"Mathematics"},{"key":"3_CR18","doi-asserted-by":"crossref","unstructured":"Chen, X., Zhou, X., Zhang, H., Sun, M., Poor, H.V.: Client selection for wireless federated learning with data and latency heterogeneity. IEEE Internet Things J. 11(19), 32:183\u201332:196 (2024)","DOI":"10.1109\/JIOT.2024.3425757"},{"key":"3_CR19","doi-asserted-by":"crossref","unstructured":"Chen, H., Frikha, A., Krompass, D., Gu, J., Tresp, V.: FRAug: tackling federated learning with Non-IID features via representation augmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (2023)","DOI":"10.1109\/ICCV51070.2023.00447"},{"key":"3_CR20","unstructured":"Cho, Y.J., Wang, J., Joshi, G.: Towards understanding biased client selection in federated learning. In: International Conference on Artificial Intelligence and Statistics, AISTATS, ser. Proceedings of Machine Learning Research (2022)"},{"key":"3_CR21","doi-asserted-by":"crossref","unstructured":"Liu, Z., Chen, Y., Yu, H., Liu, Y., Cui, L.: GTG-Shapley: efficient and accurate participant contribution evaluation in federated learning. ACM Trans. Intell. Syst. Technol. 13(4) (2022)","DOI":"10.1145\/3501811"},{"key":"3_CR22","doi-asserted-by":"crossref","unstructured":"Auer, P., Cesa-Bianchi, N., Fischer, P.: Finite-time analysis of the multiarmed bandit problem. Mach. Learn. 47(2) (2002)","DOI":"10.1023\/A:1013689704352"},{"key":"3_CR23","unstructured":"McMahan, B., Moore, E., Ramage, D., Hampson, S., y\u00a0Arcas, B.A.: Communication-efficient learning of deep networks from decentralized data. In: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, ser. Proceedings of Machine Learning Research (2017)"},{"key":"3_CR24","unstructured":"Xiao, H., Rasul, K., Vollgraf, R.: Fashion-MNIST: a novel image dataset for benchmarking machine learning algorithms. CoRR, abs\/1708.07747 (2017)"},{"issue":"11","key":"3_CR25","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y Lecun","year":"1998","unstructured":"Lecun, Y., Bottou, L.: Gradient-based learning applied to document recognition. Proc. IEEE 86(11), 2278\u20132324 (1998)","journal-title":"Proc. IEEE"},{"key":"3_CR26","unstructured":"Krizhevsky, A., Hinton, G.: Learning multiple layers of features from tiny images. Handbook of Systemic Autoimmune Diseases, vol.\u00a01, no.\u00a04 (2009)"}],"container-title":["Lecture Notes in Computer Science","Web and Big Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5716-5_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T13:06:53Z","timestamp":1769087213000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5716-5_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819557158","9789819557165"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5716-5_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"23 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"APWeb-WAIM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shenyang","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"apwebwaim2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/apweb2025.sau.edu.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}