Learning Markov Chain Models from Sequential Data Under Local Differential Privacy
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-51476-0_18
Reference32 articles.
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3. Cheng, Y., Qiao, Y., Yang, J.: An improved Markov method for prediction of user mobility. In: 2016 12th International Conference on Network and Service Management (CNSM), pp. 394–399. IEEE (2016)
4. Cormode, G., Jha, S., Kulkarni, T., Li, N., Srivastava, D., Wang, T.: Privacy at scale: local differential privacy in practice. In: Proceedings of the 2018 International Conference on Management of Data, pp. 1655–1658. ACM (2018)
5. Cunningham, T., Cormode, G., Ferhatosmanoglu, H., Srivastava, D.: Real-world trajectory sharing with local differential privacy. Proc. VLDB Endow. 14(11), 2283–2295 (2021)
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