Data Poisoning Attacks in Gossip Learning

Author:

Pham Alexandre,Potop-Butucaru Maria,Tixeuil Sébastien,Fdida Serge

Publisher

Springer Nature Switzerland

Reference19 articles.

1. Belal, Y., Bellet, A., Mokhtar, S.B., Nitu, V.: PEPPER: empowering user-centric recommender systems over gossip learning. In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 6(3), 101:1–101:27, September 2022

2. Beltrán, E.T.M., Pérez, M.Q., Sánchez, P.M.S., Bernal, S.L., Bovet, G., Pérez, M.G., Pérez, G.M., Celdrán, A.H.: Decentralized federated learning: fundamentals, state of the art, frameworks, trends, and challenges. IEEE Commun. Surv. Tutor., 1 (2023)

3. Bernstein, J., Wang, Y.-X., Azizzadenesheli, K., Anandkumar, A.: signSGD: compressed optimisation for non-convex problems. In: Proceedings of the 35th International Conference on Machine Learning, pp. 560–569. PMLR, July 2018

4. Bernstein, J., Zhao, J., Azizzadenesheli, K., Anandkumar, A.: signSGD with majority vote is communication efficient and fault tolerant. In: International Conference on Learning Representations, September 2018

5. Danner, G., Hegedűs, I., Jelasity, M.: Improving gossip learning via limited model merging. In: Advances in Computational Collective Intelligence, Communications in Computer and Information Science, pp. 351–363. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-41774-0_28

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