{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/fedlab-a-flexible-federated-learning","title":"FedLab: A Flexible Federated Learning Framework","arxiv_id":"2107.11621","date":"2021-07-24","proceeding":null,"authors":["Dun Zeng","Siqi Liang","Xiangjing Hu","Hui Wang","Zenglin Xu"],"abstract":"Federated learning (FL) is a machine learning field in which researchers try to facilitate model learning process among multiparty without violating privacy protection regulations. Considerable effort has been invested in FL optimization and communication related researches. In this work, we introduce \\texttt{FedLab}, a lightweight open-source framework for FL simulation. The design of \\texttt{FedLab} focuses on FL algorithm effectiveness and communication efficiency. Also, \\texttt{FedLab} is scalable in different deployment scenario. We hope \\texttt{FedLab} could provide flexible API as well as reliable baseline implementations, and relieve the burden of implementing novel approaches for researchers in FL community.","url_abs":"https://arxiv.org/abs/2107.11621v4","url_pdf":"https://arxiv.org/pdf/2107.11621v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"fedlab-a-flexible-federated-learning","repo_url":"https://github.com/SMILELab-FL/FedLab","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"federated-learning","task_name":"Federated Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2107.11621","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}