Byzantine-resilient decentralized network learning

Author:

Yang Yaohong,Wang LeiORCID

Publisher

Springer Science and Business Media LLC

Subject

Statistics and Probability

Reference29 articles.

1. Bellet, A., Guerraoui, R., Taziki, M., & Tommasi, M. (2018). Personalized and private peer-to-peer machine learning. In International conference on artificial intelligence and statistics (pp. 473–481).

2. Blanchard, P., El Mhamdi, E.M., Guerraoui, R., & Stainer, J. (2017). Machine learning with adversaries: Byzantine tolerant gradient descent. Advances in Neural Information Processing Systems (pp. 119–129).

3. Che, C., Li, X., Chen, C., He, X., & Zheng, Z. (2022). A decentralized federated learning framework via committee mechanism with convergence guarantee. IEEE Transactions on Parallel and Distributed Systems, 33(12), 4783–4800.

4. Cheu, A., Smith, A., Ullman, J., Zeber, D., & Zhilyaev, M. (2019). Distributed differential privacy via shuffling. In Annual international conference on the theory and applications of cryptographic techniques (pp. 375–403).

5. Colin, I., Bellet, A., Salmon, J., & Clémençon, S. (2016). Gossip dual averaging for decentralized optimization of pairwise functions. In International conference on machine learning (pp. 1388–1396).

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