Shuang Song
I work on differential privacy and machine learning.
Prior to joining Google, I received my PhD from UC San Diego, advised by Prof. Kamalika Chaudhuri.
My webpage.
Authored Publications
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Google
EANA: Reducing Privacy Risk on Large-scale Recommendation Models
Devora Berlowitz
Mei Chen
QiQi Xue
Steve Chien
16th ACM Conference on Recommender Systems (2022)
Practical and Private (Deep) Learning without Sampling or Shuffling
Preview
Om Thakkar
Abhradeep Thakurta
38th International Conference on Machine Learning (ICML 2021) (2021) (to appear)
Private Alternating Least Squares: (Nearly) OptimalPrivacy/Utility Trade-off for Matrix Completion
Abhradeep Guha Thakurta
Li Zhang
Walid Krichene
NA, NA (2021), NA
Evading the Curse of Dimensionality in Unconstrained Private Generalized Linear Problems
Thomas Steinke
Om Thakkar
Abhradeep Guha Thakurta
24th International Conference on Artificial Intelligence and Statistics (AISTATS 2021) (2020)
Scalable Private Learning with PATE
Ilya Mironov
Ananth Raghunathan
Kunal Talwar
International Conference on Learning Representations (ICLR) (2018)
