{"type":"ScholarlyArticle","title":"Fedstellar: A Platform for Training Models in a Privacy-preserving and Decentralized Fashion","authors":[{"name":"Enrique Tomás Martínez Beltrán","slug":"enrique-tomas-martinez-beltran","given":"Enrique Tomás","family":"Martínez Beltrán","affiliation":"Department of Information and Communications Engineering , University of Murcia , 30100 , Spain"},{"name":"Pedro Miguel Sánchez Sánchez","slug":"pedro-miguel-sanchez-sanchez","given":"Pedro Miguel","family":"Sánchez Sánchez","affiliation":"Department of Information and Communications Engineering , University of Murcia , 30100 , Spain"},{"name":"Sergio López Bernal","slug":"sergio-lopez-bernal","given":"Sergio","family":"López Bernal","affiliation":"Department of Information and Communications Engineering , University of Murcia , 30100 , Spain"},{"name":"Gérôme Bovet","slug":"gerome-bovet","given":"Gérôme","family":"Bovet","affiliation":"Cyber-Defence Campus , Armasuisse Science and Technology , 3602 Thun , Switzerland"},{"name":"Manuel Gil Pérez","slug":"manuel-gil-perez","given":"Manuel","family":"Gil Pérez","affiliation":"Department of Information and Communications Engineering , University of Murcia , 30100 , Spain"},{"name":"Gregorio Martínez Pérez","slug":"gregorio-martinez-perez","given":"Gregorio","family":"Martínez Pérez","affiliation":"Department of Information and Communications Engineering , University of Murcia , 30100 , Spain"},{"name":"Alberto Huertas Celdrán","slug":"alberto-huertas-celdran","given":"Alberto","family":"Huertas Celdrán","affiliation":"Communication Systems Group , Department of Informatics (IFI) , University of Zurich , 8050 Zürich , Switzerland"}],"abstract":"This paper presents Fedstellar, a platform for training decentralized Federated Learning (FL) models in heterogeneous topologies in terms of the number of federation participants and their connections. Fedstellar allows users to build custom topologies, enabling them to control the aggregation of model parameters in a decentralized manner. The platform offers a Web application for creating, managing, and connecting nodes to ensure data privacy and provides tools to measure, monitor, and analyze the performance of the nodes. The paper describes the functionalities of Fedstellar and its potential applications. To demonstrate the applicability of the platform, different use cases are presented in which decentralized, semi-decentralized, and centralized architectures are compared in terms of model performance, convergence time, and network overhead when collaboratively classifying hand-written digits using the MNIST dataset.","doi":"10.24963/ijcai.2023/838","url":"https://ijcai.org/proceedings/2023/838","pdf":"https://ijcai.org/proceedings/2023/0838.pdf","markdown":"https://ijcai.org/proceedings/2023/838.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/838","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Demo Track","track":"Demo Track","number":838,"pages":{"first":7154,"last":7157},"keywords":["Machine Learning: ML: Applications","Machine Learning: ML: Evaluation","Machine Learning: ML: Federated learning","Machine Learning: ML: Classification"],"videos":[],"references":[{"position":1,"raw":"[Barbieri et al., 2022] Luca Barbieri, Stefano Savazzi, Mat- tia Brambilla, and Monica Nicoli. 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