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Specifically, we propose a separate architecture for sequence reconstruction networks (SEPRE) which partitions the network into two parts: a shared part and a standalone part, better suited for federated learning schemes. In tandem, we propose a novel partial shared federated learning scheme that employs a mask strategy to alleviate communication overhead and produce personalized local models to address the statistical heterogeneity of data among clients. This scheme dictates that a subset of weights is communicated between clients and servers for collaborative training, while the remaining weights are trained exclusively locally. To evaluate the effectiveness of FeadSeq, we conduct extensive experiments on both system logs and business process event logs. The results affirm the superiority of FeadSeq over existing personalized federated learning algorithms, showcasing not only improved performance but also reduced communication overhead.<\/jats:p>","DOI":"10.1145\/3742896","type":"journal-article","created":{"date-parts":[[2025,6,5]],"date-time":"2025-06-05T10:22:06Z","timestamp":1749118926000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["FeadSeq: A Personalized Federated Anomaly Detection Framework for Discrete Event Sequences"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8979-6847","authenticated-orcid":false,"given":"Wei","family":"Guan","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiao Tong\u00a0University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0036-9436","authenticated-orcid":false,"given":"Jian","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiao Tong\u00a0University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-6430-6303","authenticated-orcid":false,"given":"Haiyan","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Shanghai for Science\u00a0and Technology, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7905-1182","authenticated-orcid":false,"given":"Yang","family":"Gu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiao Tong\u00a0University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7775-1740","authenticated-orcid":false,"given":"Shiyou","family":"Qian","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Shanghai Jiao Tong\u00a0University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,7,9]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/3214303"},{"key":"e_1_3_2_3_2","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1007\/978-3-031-34204-2_41","volume-title":"Proceedings of the International Conference on Engineering Applications of Neural Networks","author":"Al-Saedi Ahmed A.","year":"2023","unstructured":"Ahmed A. 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