@ARTICLE{Liu2019a,
  author = {Fang Liu},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  title={Generalized Gaussian Mechanism for Differential Privacy},
  year={2019},
  volume={31},
  number={4},
  pages={747-756},
  url={https://doi.org/10.1109/TKDE.2018.2845388}
}

@InProceedings{Dwork2006a,
  author={Cynthia Dwork
    and Frank McSherry
    and Kobbi Nissim
    and Adam Smith},
  editor={Shai Halevi
    and Tal Rabin},
  title={Calibrating Noise to Sensitivity in Private Data Analysis},
  booktitle={Theory of Cryptography},
  year={2006},
  publisher={Springer Berlin Heidelberg},
  address={Berlin, Heidelberg},
  pages={265--284},
  isbn={978-3-540-32732-5},
  url={https://doi.org/10.1007/11681878_14}
}

@ARTICLE{Liu2019b,
  author={Fang Liu},
  journal={Transactions on Data Privacy},
  title={Statistical Properties of Sanitized Results from Differentially Private Laplace Mechanism with Univariate Bounding Constraints},
  year={2019},
  volume={12},
  number={3},
  pages={169-195},
  url={http://www.tdp.cat/issues16/tdp.a316a18.pdf}
}

@inproceedings{Smith2011a,
  author = {Adam Smith},
  title = {Privacy-Preserving Statistical Estimation with Optimal Convergence Rates},
  year = {2011},
  isbn = {9781450306911},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/1993636.1993743},
  doi = {10.1145/1993636.1993743},
  booktitle = {Proceedings of the Forty-Third Annual ACM Symposium on Theory of Computing},
  pages = {813–822},
  numpages = {10},
  keywords = {statistical inference, differential privacy, asymptotic distribution},
  location = {San Jose, California, USA},
  series = {STOC '11}
}

@inproceedings{Kifer2011,
  author = {Daniel Kifer
    and Ashwin Machanavajjhala},
  title = {No Free Lunch in Data Privacy},
  year = {2011},
  isbn = {9781450306614},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  url = {https://doi.org/10.1145/1989323.1989345},
  doi = {10.1145/1989323.1989345},
  booktitle = {Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data},
  pages = {193–204},
  numpages = {12},
  keywords = {differential privacy, privacy},
  location = {Athens, Greece},
  series = {SIGMOD '11}
}

@article{chaudhuri2011,
  author  = {Kamalika Chaudhuri
    and Claire Monteleoni
    and Anand D. Sarwate},
  title   = {Differentially Private Empirical Risk Minimization},
  journal = {Journal of Machine Learning Research},
  year    = {2011},
  volume  = {12},
  number  = {29},
  pages   = {1069-1109},
  url     = {https://jmlr.org/papers/v12/chaudhuri11a.html}
}

@InProceedings{Kifer2012,
  title = 	 {Private Convex Empirical Risk Minimization and High-dimensional Regression},
  author = 	 {Daniel Kifer
    and Adam Smith
    and Abhradeep Thakurta},
  booktitle = {Proceedings of the 25th Annual Conference on Learning Theory},
  pages = 	 {25.1--25.40},
  year = 	 {2012},
  editor = 	 {Shie Mannor
    and Nathan Srebro
    and Robert C. Williamson},
  volume = 	 {23},
  series = 	 {Proceedings of Machine Learning Research},
  address = 	 {Edinburgh, Scotland},
  month = 	 {25--27 Jun},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v23/kifer12/kifer12.pdf},
  url = 	 {https://proceedings.mlr.press/v23/kifer12.html}
}

@article{DPtextbook,
  author = {Cynthia Dwork and
    Aaron Roth},
  title = {The Algorithmic Foundations of Differential Privacy},
  year = {2014},
  issue_date = {August 2014},
  publisher = {Now Publishers Inc.},
  address = {Hanover, MA, USA},
  volume = {9},
  number = {3–4},
  issn = {1551-305X},
  url = {https://doi.org/10.1561/0400000042},
  journal = {Foundations and Trends in Theoretical Computer Science},
  month = {aug},
  pages = {211–407},
  numpages = {197}
}

@ARTICLE{Chapelle2007,
  author={Olivier Chapelle},
  journal={Neural Computation},
  title={Training a Support Vector Machine in the Primal},
  year={2007},
  volume={19},
  number={5},
  pages={1155-1178},
  doi={10.1162/neco.2007.19.5.1155}
}

@inproceedings{Rahimi2007,
 author = {Ali Rahimi and
    Benjamin Recht},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {J Platt and D Koller and Y Singer and S Roweis},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Random Features for Large-Scale Kernel Machines},
 url = {https://proceedings.neurips.cc/paper/2007/file/013a006f03dbc5392effeb8f18fda755-Paper.pdf},
 volume = {20},
 year = {2007}
}

@inproceedings{Rahimi2008,
 author = {Ali Rahimi and Benjamin Recht},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {D Koller and D Schuurmans and Y Bengio and L Bottou},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning},
 url = {https://proceedings.neurips.cc/paper/2008/file/0efe32849d230d7f53049ddc4a4b0c60-Paper.pdf},
 volume = {21},
 year = {2008}
}


@InProceedings{Gillenwater2021,
  title = 	 {Differentially Private Quantiles},
  author =       {Jennifer Gillenwater and Matthew Joseph and Alex Kulesza},
  booktitle = 	 {Proceedings of the 38th International Conference on Machine Learning},
  pages = 	 {3713--3722},
  year = 	 {2021},
  editor = 	 {Marina Meila and Tong Zhang},
  volume = 	 {139},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {18--24 Jul},
  publisher =    {PMLR},
  url = 	 {http://proceedings.mlr.press/v139/gillenwater21a/gillenwater21a.pdf}
}

@inproceedings{Chaudhuri2009,
 author = {Kamalika Chaudhuri and
    Claire Monteleoni},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {D Koller and D Schuurmans and Y Bengio and L Bottou},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Privacy-preserving logistic regression},
 url = {https://proceedings.neurips.cc/paper/2008/file/8065d07da4a77621450aa84fee5656d9-Paper.pdf},
 volume = {21},
 year = {2009}
}

@INPROCEEDINGS{McSherry2007,
  author={Frank McSherry and
    Kunal Talwar},
  booktitle={48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07)},
  title={Mechanism Design via Differential Privacy},
  year={2007},
  volume={},
  number={},
  pages={94-103},
  doi={10.1109/FOCS.2007.66}
}

@InProceedings{Dwork2006b,
  author={Cynthia Dwork
    and Krishnaram Kenthapadi
    and Frank McSherry
    and Ilya Mironov
    and Moni Naor},
  editor={Serge Vaudenay},
  title={Our Data, Ourselves: Privacy Via Distributed Noise Generation},
  booktitle={Advances in Cryptology - EUROCRYPT 2006},
  year={2006},
  publisher={Springer Berlin Heidelberg},
  address={Berlin, Heidelberg},
  pages={486--503},
  isbn={978-3-540-34547-3},
  doi={10.1007/11761679_29}
}

@INPROCEEDINGS{Machanavajjhala2008,
  author={Ashwin Machanavajjhala
    and Daniel Kifer
    and John Abowd
    and Johannes Gehrke
    and Lars Vilhuber},
  booktitle={2008 IEEE 24th International Conference on Data Engineering},
  title={Privacy: Theory meets Practice on the Map},
  year={2008},
  volume={},
  number={},
  pages={277-286},
  doi={10.1109/ICDE.2008.4497436}
}

@INPROCEEDINGS{Yang2005,
  author={Xulei Yang
    and Qing Song
    and A. Cao},
  booktitle={Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.},
  title={Weighted support vector machine for data classification},
  year={2005},
  volume={2},
  number={},
  pages={859-864 vol. 2},
  doi={10.1109/IJCNN.2005.1555965}
}


@InProceedings{Balle2018,
  title = {Improving the {G}aussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising},
  author = {Balle, Borja and Wang, Yu-Xiang},
  booktitle = {Proceedings of the 35th International Conference on Machine Learning},
  pages = {394--403},
  year = {2018},
  editor = {Dy, Jennifer and Krause, Andreas},
  volume = {80},
  series = {Proceedings of Machine Learning Research},
  month = {10--15 Jul},
  publisher = {PMLR},
  url = 	 {https://proceedings.mlr.press/v80/balle18a.html},
}

