{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T07:27:34Z","timestamp":1761895654331,"version":"build-2065373602"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012492","name":"Youth Innovation Promotion Association","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012492","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017413","name":"Innovation Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100017413","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,30]]},"DOI":"10.1109\/icme59968.2025.11209282","type":"proceedings-article","created":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T17:57:42Z","timestamp":1761847062000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["FairFHTL: Achieving Task-Agnostic Fairness in Federated Hetero-Task Learning"],"prefix":"10.1109","author":[{"given":"Teng","family":"Zhang","sequence":"first","affiliation":[{"name":"Chinese Academy of Sciences,Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Institute of Computing Technology,Beijing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiqiang","family":"Chen","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences,Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Institute of Computing Technology,Beijing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinlong","family":"Jiang","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences,Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Institute of Computing Technology,Beijing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wuliang","family":"Huang","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences,Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Institute of Computing Technology,Beijing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Chen","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences,Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Institute of Computing Technology,Beijing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenlong","family":"Gao","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences,Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Institute of Computing Technology,Beijing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhirui","family":"Wang","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences,Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Institute of Computing Technology,Beijing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bingjie","family":"Yan","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences,Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Institute of Computing Technology,Beijing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1273","article-title":"Communication-Efficient Learning of Deep Networks from Decentralized Data","volume-title":"Proceedings of the 20th International Conference on Artificial Intelligence and Statistics","author":"McMahan"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3510033"},{"article-title":"A Benchmark for Federated Hetero-Task Learning","year":"2023","author":"Yao","key":"ref3"},{"key":"ref4","article-title":"Equality of opportunity in supervised learning","volume":"29","author":"Hardt","year":"2016","journal-title":"Advances in neural information processing systems"},{"key":"ref5","first-page":"4615","article-title":"Agnostic federated learning","volume-title":"Proceedings of the 36th International Conference on Machine Learning","author":"Mohri"},{"article-title":"Fair Resource Allocation in Federated Learning","volume-title":"Proc. the 8th International Conference on Learning Representations","author":"Li","key":"ref6"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2022.3169117"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s11390-024-3639-x"},{"article-title":"Fair resource allocation in multi-task learning","volume-title":"Forty-first International Conference on Machine Learning","author":"Ban","key":"ref9"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3263594"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/223"},{"key":"ref12","first-page":"4427","article-title":"Federated multi-task learning","volume-title":"Proc. the 31st International Conference on Neural Information Processing Systems","author":"Smith"},{"key":"ref13","first-page":"15434","article-title":"Federated multi-task learning under a mixture of distributions","volume-title":"Proc. the 35th International Conference on Neural Information Processing Systems","author":"Marfoq"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW59228.2023.00532"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00535"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00195"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467254"},{"key":"ref18","first-page":"429","article-title":"Federated Optimization in Heterogeneous Networks","volume-title":"Proceedings of Machine Learning and Systems","volume":"2","author":"Li"},{"key":"ref19","first-page":"21394","article-title":"Personalized federated learning with moreau envelopes","volume-title":"Proceedings of the 34th International Conference on Neural Information Processing Systems","author":"Dinh"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00391"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33715-4_54"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.119"}],"event":{"name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","start":{"date-parts":[[2025,6,30]]},"location":"Nantes, France","end":{"date-parts":[[2025,7,4]]}},"container-title":["2025 IEEE International Conference on Multimedia and Expo (ICME)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11208895\/11208897\/11209282.pdf?arnumber=11209282","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T05:55:28Z","timestamp":1761890128000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11209282\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/icme59968.2025.11209282","relation":{},"subject":[],"published":{"date-parts":[[2025,6,30]]}}}