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Fashion-MNIST: a novel image dataset for benchmarking machine learning algorithms. arXiv:1708.07747. 2017."},{"journal-title":"Learning multiple layers of features from tiny images","year":"2009","author":"Krizhevsky","key":"ref40"},{"journal-title":"26th Annual Conference on Neural Information Processing Systems 2012","author":"Krizhevsky","key":"ref41"},{"key":"ref42","first-page":"1273","author":"McMahan","year":"2017 Apr 20\u201322","journal-title":"Proceedings of the 20th International Conference on Artificial Intelligence and Statistics"},{"key":"ref43","unstructured":"Arivazhagan MG, Aggarwal V, Singh AK, Choudhary S. Federated learning with personalization layers. arXiv:1912.00818. 2019."},{"key":"ref44","unstructured":"Liang PP, Liu T, Liu Z, Allen NB, Auerbach RP, Brent D, et al. Think locally, act globally: federated learning with local and global representations. arXiv:2001.01523. 2020."},{"key":"ref45","unstructured":"Oh J, Kim S, Yun SY. FedBABU: towards enhanced representation for federated image classification. arXiv:2106.06042. 2021."},{"key":"ref46","series-title":"Proceedings of the 36th International Conference on Neural Information Processing Systems","first-page":"38831","article-title":"FedSR: a simple and effective domain generalization method for federated learning","author":"Nguyen","year":"2022 Nov 28\u2013Dec 9"}],"container-title":["Computers, Materials &amp; Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-83-1\/TSP_CMC_60709\/TSP_CMC_60709.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T06:36:42Z","timestamp":1763102202000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v83n1\/60101"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":46,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.060709","relation":{},"ISSN":["1546-2226"],"issn-type":[{"type":"electronic","value":"1546-2226"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"2024-11-07","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-01-21","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-03-26","order":2,"name":"published","label":"Published Online","group":{"name":"publication_history","label":"Publication History"}}]}}