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Federated learning is a new learning paradigm that decouples data collection and model training via multi-party computation and model aggregation.
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Fan, F.X., Ma, Y., Dai, Z., Tan, C., Low, B.K.H.: Fedhql: Federated heterogeneous q-learning. In: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, pp. 2810–2812 (2023)
2023
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Tan, Y., Chen, C., Zhuang, W., Dong, X., Lyu, L., Long, G.: Is heterogeneity notorious? taming heterogeneity to handle test-time shift in federated learning. In: Thirty-seventh Conference on Neural Information Processing Systems (2023)
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2023
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Khalatbarisoltani, A., Boulon, L., Hu, X.: Integrating model predictive control with federated reinforcement learning for decentralized energy management of fuel cell vehicles. IEEE Transactions on Intelligent Transportation Systems (2023)
2023
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Qiu, D., Xue, J., Zhang, T., Wang, J., Sun, M.: Federated reinforcement learning for smart building joint peer-to-peer energy and carbon allowance trading. Applied Energy 333
2023
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Fan, K., Hong, J., Li, W., Zhao, X., Li, H., Yang, Y.: Flsg: A novel defense strategy against inference attacks in vertical federated learning. IEEE Internet of Things Journal (2023)
2023
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Park, S., Han, S., Wu, F., Kim, S., Zhu, B., Xie, X., Cha, M.: Feddefender: Client-side attack-tolerant federated learning. In: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 1850–1861 (2023)
2023
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Chang, Y., Zhang, K., Gong, J., Qian, H.: Privacy-preserving federated learning via functional encryption, revisited. IEEE Transactions on Information Forensics and Security 18
2023
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Hijazi, N.M., Aloqaily, M., Guizani, M., Ouni, B., Karray, F.: Secure federated learning with fully homomorphic encryption for iot communications. IEEE Internet of Things Journal (2023)
2023
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2023
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Tan, Y., Liu, Y., Long, G., Jiang, J., Lu, Q., Zhang, C.: Federated learning on non-iid graphs via structural knowledge sharing. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, pp. 9953–9961 (2023)
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Yuan, W., Yin, H., Wu, F., Zhang, S., He, T., Wang, H.: Federated unlearning for on-device recommendation. In: Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, pp. 393–401 (2023)
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Chen, Z., Li, W., Xing, X., Yuan, Y.: Medical federated learning with joint graph purification for noisy label learning. Medical Image Analysis 90
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Zhu, M., Chen, Z., Yuan, Y.: FedDM: Federated weakly supervised segmentation via annotation calibration and gradient de-conflicting. IEEE Transactions on Medical Imaging (2023)
2023
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