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+@inproceedings{abowd2008protective,
+  title={How protective are synthetic data?},
+  author={Abowd, John M and Vilhuber, Lars},
+  booktitle={International Conference on Privacy in Statistical Databases},
+  pages={239--246},
+  year={2008},
+  organization={Springer}
+}
+@inproceedings{jordon2018pate,
+  title={PATE-GAN: Generating synthetic data with differential privacy guarantees},
+  author={Jordon, James and Yoon, Jinsung and Van Der Schaar, Mihaela},
+  booktitle={International conference on learning representations},
+  year={2018}
+}
+@inproceedings{abay2019privacy,
+  title={Privacy preserving synthetic data release using deep learning},
+  author={Abay, Nazmiye Ceren and Zhou, Yan and Kantarcioglu, Murat and Thuraisingham, Bhavani and Sweeney, Latanya},
+  booktitle={Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10--14, 2018, Proceedings, Part I 18},
+  pages={510--526},
+  year={2019},
+  organization={Springer}
+}
+
+@inproceedings{ben2002theoretical,
+  title={A theoretical framework for learning from a pool of disparate data sources},
+  author={Ben-David, Shai and Gehrke, Johannes and Schuller, Reba},
+  booktitle={Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining},
+  pages={443--449},
+  year={2002}
+}
+
+@inproceedings{chen2020differential,
+  title={Differential privacy protection against membership inference attack on machine learning for genomic data},
+  author={Chen, Junjie and Wang, Wendy Hui and Shi, Xinghua},
+  booktitle={BIOCOMPUTING 2021: Proceedings of the Pacific Symposium},
+  pages={26--37},
+  year={2020},
+  organization={World Scientific}
+}
+@article{rahman2018membership,
+  title={Membership inference attack against differentially private deep learning model.},
+  author={Rahman, Md Atiqur and Rahman, Tanzila and Lagani{\`e}re, Robert and Mohammed, Noman and Wang, Yang},
+  journal={Trans. Data Priv.},
+  volume={11},
+  number={1},
+  pages={61--79},
+  year={2018}
+}
+
+@article{kivinen1997exponentiated,
+  title={Exponentiated gradient versus gradient descent for linear predictors},
+  author={Kivinen, Jyrki and Warmuth, Manfred K},
+  journal={information and computation},
+  volume={132},
+  number={1},
+  pages={1--63},
+  year={1997},
+  publisher={Elsevier}
+}
+
 @article{breiman2001random,
   title={Random forests},
   author={Breiman, Leo},