Our results show that the Class-Balanced FL can effectively defend against different poisoning attacks, including our Class Imbalance Attack. The rest of this ...
We propose the Contribution-wise byzantine-robust aggregation rule, which dynamically assigns the heavyweight to the client having a high potential contribution ...
Oct 25, 2023 · Abstract. Federated learning (FL) is a promising approach that allows many clients jointly train a model without sharing the raw data.
Aug 17, 2024 · Contribution-Wise Byzantine-Robust Aggregation for Class-Balanced Federated Learning. January 2023. DOI:10.2139/ssrn.4612709. Authors: Yanli Li ...
May 3, 2024 · This paper summarizes the experience of teaching an introductory course to programming by using a correctness by construction approach at ...
Contribution-wise Byzantine-robust aggregation for Class-Balanced Federated Learning. https://doi.org/10.1016/j.ins.2024.120475 ·. Journal: Information ...
Contribution-Wise Byzantine-Robust Aggregation for Class-Balanced Federated Learning. https://doi.org/10.2139/ssrn.4612709. Journal: 2023. Publisher: Elsevier ...
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What is aggregation in federated learning?
What is secure aggregation in federated learning?
Sep 26, 2024 · In this paper, we present a novel Byzantine-robust aggregation algorithm to enhance the security of Decentralized Federated Learning ...
Jul 13, 2024 · In this paper, we propose a new algorithm called BALANCE (Byzantine-robust averaging through local similarity in decentralization) to defend.
Federated learning presents massive potential for privacy-friendly collaboration. However, feder- ated learning is deeply threatened by byzantine.