FedDefender: Client-Side Attack-Tolerant Federated Learning
Comments KDD'23 research track accepted
期刊&会议
ACM SIGKDD Conference on Knowledge Discovery and Data Mining · 会议 · Data Mining
Comments KDD'23 research track accepted
Comments Accepted to Workshop on Graph Learning Benchmarks at KDD 2023
Comments In Advances in Knowledge Discovery and Data Mining 2023 (PAKDD 2023)
Comments Accepted in KDD'23
Comments Accepted by KDD 2023
Comments KDD 2023
Comments Accepted at SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023
Comments 11 pages, 6 figures, 5 tables, camera ready version of SIGKDD 2023
Comments This paper is accepted by KDD'23
Journal ref 2023 ACM SIGKDD Workshop on Causal Discovery, Prediction and Decision
Comments Accepted by KDD 2023
Comments 2023 9th ACM SIGKDD International Workshop on Mining and Learning From Time Series (MiLeTS 2023)
Comments Accepted by SIGKDD Explorations 2023, Volume 25, Issue 1
Journal ref KDD 2023
Comments Accepted in KDD 2023; The website is at https://seqml.github.io/marl4fin
Comments To appear in KDD 2023
Comments KDD'23 conference (main research track). (*) These authors contributed equally
Comments Accepted by KDD'23
Comments KDD 2023 accepted
Journal ref KDD 2023: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Comments Published as a conference paper at KDD KiML 2023
Comments Accepted to KDD 2023 (Research Track)
Comments SIGKDD 2023
Comments KDD 2023
Comments SIGKDD 2023
Comments Accepted at KDD 2023. This work has already been deployed on the display advertising system in Alibaba, bringing substantial economic gains
Comments Accepted by KDD 2023
Comments Accepted by KDD 2023
Comments Accepted by KDD 2023. Detailed discussions can be found in https://openreview.net/forum?id=P1Worw-M1Tf&referrer=[the%20profile%20of%20Minqi%20Jiang](/profile?id=~Minqi_Jiang2)
Comments KDD 2023
Comments To appear in Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 23)