Approximate k-Nearest Neighbor Query over Spatial Data Federation

Author:

Zhang Kaining,Tong Yongxin,Shi Yexuan,Zeng Yuxiang,Xu Yi,Chen Lei,Zhou Zimu,Xu Ke,Lv Weifeng,Zheng Zhiming

Publisher

Springer Nature Switzerland

Reference28 articles.

1. Amap: https://lbs.amap.com/. Accessed 30 Jan 2023

2. Bater, J., Elliott, G., Eggen, C., Goel, S., Kho, A.N., Rogers, J.: SMCQL: secure query processing for private data networks. PVLDB 10(6), 673–684 (2017)

3. Bater, J., He, X., Ehrich, W., Machanavajjhala, A., Rogers, J.: Shrinkwrap: efficient SQL query processing in differentially private data federations. PVLDB 12(3), 307–320 (2018)

4. Bater, J., Park, Y., He, X., Wang, X., Rogers, J.: SAQE: practical privacy-preserving approximate query processing for data federations. PVLDB 13(11), 2691–2705 (2020)

5. Bonawitz, K., et al.: Practical secure aggregation for privacy-preserving machine learning. In: CCS, pp. 1175–1191 (2017)

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1. A survey on federated learning: a perspective from multi-party computation;Frontiers of Computer Science;2023-12-02

2. Federated $k$-Dominant Skyline: An Efficient Approach Under Differential Privacy;2023 5th International Conference on Data-driven Optimization of Complex Systems (DOCS);2023-09-22

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