Flip: A provable defense framework for backdoor mitigation in federated learning

K Zhang, G Tao, Q Xu, S Cheng, S An, Y Liu… - arXiv preprint arXiv …, 2022 - arxiv.org
Federated Learning (FL) is a distributed learning paradigm that enables different parties to
train a model together for high quality and strong privacy protection. In this scenario …
被引用次数：35 相关文章

[引用][C] FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning

K Zhang, G Tao - 2023 - par.nsf.gov

FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning

K Zhang, G Tao, Q Xu, S Cheng, S An… - International …, 2023 - research.ibm.com
Federated Learning (FL) is a distributed learning paradigm that enables different parties to
train a model together for high quality and strong privacy protection. In this scenario …
[PDF] purdue.edu

[PDF][PDF] FLIP: AProvable DEFENSE FRAMEWORK FOR BACKDOOR MITIGATION IN FEDERATED LEARNING

K Zhang, G Tao, Q Xu, S Cheng, S An, Y Liu, S Feng… - cs.purdue.edu
Federated Learning (FL) is a distributed learning paradigm that enables different parties to
train a model together for high quality and strong privacy protection. In this scenario …

FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning

K Zhang, G Tao, Q Xu, S Cheng, S An, Y Liu… - arXiv e …, 2022 - ui.adsabs.harvard.edu
Federated Learning (FL) is a distributed learning paradigm that enables different parties to
train a model together for high quality and strong privacy protection. In this scenario …
[PDF] umass.edu

[PDF][PDF] FLIP: AProvable DEFENSE FRAMEWORK FOR BACKDOOR MITIGATION IN FEDERATED LEARNING

K Zhang, G Tao, Q Xu, S Cheng, S An, Y Liu, S Feng… - people.cs.umass.edu
Federated Learning (FL) is a distributed learning paradigm that enables different parties to
train a model together for high quality and strong privacy protection. In this scenario …
[PDF] kaiyuanzhang.com

[PDF][PDF] FLIP: AProvable DEFENSE FRAMEWORK FOR BACKDOOR MITIGATION IN FEDERATED LEARNING

K Zhang, G Tao, Q Xu, S Cheng, S An, Y Liu, S Feng… - kaiyuanzhang.com
Federated Learning (FL) is a distributed learning paradigm that enables different parties to
train a model together for high quality and strong privacy protection. In this scenario …

FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning

K Zhang, G Tao, Q Xu, S Cheng, S An, Y Liu… - … Conference on Learning … - openreview.net
Federated Learning (FL) is a distributed learning paradigm that enables different parties to
train a model together for high quality and strong privacy protection. In this scenario …
[PDF] github.io

[PDF][PDF] FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning

K Zhang, G Tao, Q Xu, S Cheng, S An, Y Liu, S Feng… - eccv22-arow.github.io
Federated Learning (FL) is a distributed learning paradigm that enables different parties to
train a model together for better quality and strong privacy protection. In this scenario …
[PDF] kaiyuanzhang.com

[PDF][PDF] FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning

K Zhang, G Tao, Q Xu, S Cheng, S An, Y Liu, S Feng… - kaiyuanzhang.com
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FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning Kaiyuan …