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1. C. X. Wang, W. P. Tay. On the Relationship Between Information-Theoretic Privacy Metrics And Probabilistic Information Privacy. arXiv preprint, submitted to IEEE Trans. Information Theory, 2023.

2. C. X. Wang, W. P. Tay. Practical Bounds of Kullback-Leibler Divergence Using Maximum Mean Dscrepancy. arXiv preprint, submitted to J. Machine Learning Research, 2022.

3. C. X. Wang, W. P. Tay. Data-driven Regularized Inference Privacy,. arXiv preprint, (in revision) submitted to IEEE Trans. Dependable Secure Computing , 2021.

4. C. X. Wang, Y. Song, W. P. Tay. Arbitrarily Strong Utility-privacy Tradeoff in Multi-agent Systems. IEEE Trans. Inf. Forensics Security, pp. 1-1, 2020.

5. Y. Song, C. X. Wang, and W. P. Tay. Compressive Privacy for a Linear Dynamical System. IEEE Trans. Inf. Forensics Security, vol. 15, no. 1, pp. 895-910, Dec. 2020.

6. Y. Xu, C. X. Wang, Y. Song, and W. P. Tay. Preserving Trajectory Privacy in Driving Data Release. Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, Singapore, May 2022.

7. C. X. Wang and W. P. Tay. Data-driven Privacy with Domain Regularization. Proc. IEEE Global Telecomm. Conf., Taipei, Taiwan, Dec. 2020.

8. C. X. Wang, W. P. Tay, and Y. Song. Maximum Privacy Under Perfect Utility in Sensor Networks. Proc. IEEE Sensor Array and Multichannel Signal Processing Workshop, Hangzhou, China, Jun. 2020.

9. C. X. Wang, Y. Song, and W. P. Tay. Preserving Parameter Privacy in Sensor Networks. Proc. IEEE Global Conf. on Signal and Information Processing, Anaheim, USA, Nov. 2018.

10. Y. Song, C. X. Wang, and W. P. Tay. Privacy-aware Kalman Filtering. Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing, Calgary, Canada, Apr. 2018.

11. Y. Song, C. X. Wang, W. P. Tay, and C. L. Law. Grid-based Belief Propagation. Int. Conf. on Indoor Positioning and Indoor Navigation, Sapporo, Japan, Sep. 2017.