A Blockchain-based Decentralized Federated Learning Framework with Committee Consensus

C. Hu, J. Jiang, and Z. Wang, “Decentralized federated learning: A segmented gossip approach,” CoRR , vol. abs/1908.07782, 2019. [Online]. Available: http://arxiv.org/abs/1908.07782

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1908

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P. Ramanan, K. Nakayama, and R. Sharma, “BAFFLE : Blockchain based aggregator free federated learning,” CoRR , vol. abs/1909.07452, 2019. [Online]. Available: http://arxiv.org/abs/1909.07452

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S. Zhou, H. Huang, W. Chen, Z. Zheng, and S. Guo, “PIRATE: A blockchain-based secure framework of distributed machine learning in 5g networks,” CoRR , vol. abs/1912.07860, 2019. [Online]. Available: http://arxiv.org/abs/1912.07860

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J. Konecný, H. B. McMahan, F. X. Yu, P. Richtárik, A. T. Suresh, and D. Bacon, “Federated learning: Strategies for improving communication efficiency,” CoRR , vol. abs/1610.05492, 2016. [Online]. Available: http://arxiv.org/abs/1610.05492

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A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” Commun. ACM , vol. 60, no. 6, pp. 84–90, 2017. [Online]. Available: http://doi.acm.org/10.1145/3065386

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X. Chen, J. Ji, C. Luo, W. Liao, and P. Li, “When machine learning meets blockchain: A decentralized, privacy-preserving and secure design,” in 2018 IEEE International Conference on Big Data (Big Data) , Dec 2018, pp. 1178–1187

2018

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I. Hegedüs, G. Danner, and M. Jelasity, “Gossip learning as a decentralized alternative to federated learning,” in Distributed Applications and Interoperable Systems - 19th IFIP WG 6.1 International Conference, DAIS 2019, Held as Part of the 14th International Federated Conference on Distributed Computing Techniques, DisCoTec 2019, Kongens Lyngby, Denmark, June 17-21, 2019, Proceedings , 2019, pp. 74–90. [Online]. Available: https://doi.org/10.1007/978-3-030-22496-7_5

2019

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Y. J. Kim and C. S. Hong, “Blockchain-based node-aware dynamic weighting methods for improving federated learning performance,” in 20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019, Matsue, Japan, September 18-20, 2019 . IEEE, 2019, pp. 1–4. [Online]. Available: https://doi.org/10.23919/APNOMS.2019.8893114

2019

Later among the works it cites.

U. Majeed and C. S. Hong, “Flchain: Federated learning via mec-enabled blockchain network,” in 20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019, Matsue, Japan, September 18-20, 2019 . IEEE, 2019, pp. 1–4. [Online]. Available: https://doi.org/10.23919/APNOMS.2019.8892848