Bio

Ergute Bao is currently a Ph.D candidate of National University of Singapore (NUS), supervised by Professor Xiaokui Xiao. He completed his B.Sc with First Class Honors in Computer Science from the Chinese University of Hong Kong (CUHK) in 2018.

Publications

• DPIS: an Enhanced Mechanism for Differentially Private SGD with Importance Sampling.
  Jianxin Wei, Ergute Bao, Xiaokui Xiao, and Yin Yang.
  The 29th ACM Conference on Computer and Communications Security (CCS), 2022. [Slides]

• Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy.
  Ergute Bao, Yizheng Zhu, Xiaokui Xiao, Yin Yang, Beng Chin Ooi, B.H.M. Tan, and K.M.M. Aung.
  48th International Conference on Very Large Data Bases (VLDB), 2022. [Technical report] [Slides]

• Synthetic Data Generation with Differential Privacy via Bayesian Networks.
  Ergute Bao, Xiaokui Xiao, Jun Zhao, Dongping Zhang, and Bolin Ding.
  Journal of Privacy and Confidentiality (JPC), 2021, Vol. 11 No. 3.

• Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy.
  Ergute Bao, Yin Yang, Xiaokui Xiao, and Bolin Ding.
  47th International Conference on Very Large Data Bases (VLDB), 2021. [Technical report]

Selected Awards

• First place in the 2020 NIST Differential Privacy Temporal Map Challenge. [news]

• Third place in the 2018 NIST Differential Privacy Synthetic Data Challenge. [news]

Academic Services

• Reviewer for ICML 2022, TKDE 2022, DASFAA 2023.