Towards Efficient and Privacy-Preserving Service QoS Prediction with Federated Learning
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-67540-0_3
Reference36 articles.
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3. Bonawitz, K., et al.: Towards federated learning at scale: system design. arXiv preprint arXiv:1902.01046 (2019)
4. Carminati, B., Ferrari, E., Tran, N.H.: A privacy-preserving framework for constrained choreographed service composition. In: 2015 IEEE International Conference on Web Services, pp. 297–304. IEEE (2015)
5. Chen, T., Bahsoon, R.: Self-adaptive and online QoS modeling for cloud-based software services. IEEE Trans. Softw. Eng. 43(5), 453–475 (2016)
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