{"type":"ScholarlyArticle","title":"Stakeholder-oriented Decision Support for Auction-based Federated Learning","authors":[{"name":"Xiaoli Tang","slug":"xiaoli-tang","given":"Xiaoli","family":"Tang","affiliation":""}],"abstract":"Auction-based federated learning (AFL) is an important area of FL incentive mechanism design. It effectively incentivizes high-quality data owners (DOs) to participate in data consumers' (DCs, i.e., servers') FL training tasks. However, AFL is still evolving, with existing methods primarily addressing optimal DC-DO matching or DC selection problems in monopoly markets. To enhance the practicality of AFL, we introduce stakeholder-oriented decision support in AFL. This facilitates optimal and strategic decision-making for all stakeholders, improving the efficiency and sustainability of the AFL ecosystem.","doi":"10.24963/ijcai.2024/972","url":"https://ijcai.org/proceedings/2024/972","pdf":"https://ijcai.org/proceedings/2024/0972.pdf","markdown":"https://ijcai.org/proceedings/2024/972.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/972","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":972,"pages":{"first":8514,"last":8515},"keywords":["DC: Machine Learning"],"videos":[],"references":[{"position":1,"raw":"[Jiao et al., 2020] Yutao Jiao, Ping Wang, Dusit Niyato, Bin Lin, and Dong In Kim. 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