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Regression with Label Differential Privacy


Dec 12, 2022
Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash Varadarajan, Chiyuan Zhang

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Private Ad Modeling with DP-SGD


Nov 21, 2022
Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash Varadarajan, Chiyuan Zhang

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Anonymized Histograms in Intermediate Privacy Models


Oct 27, 2022
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

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* Neural Information Processing Systems (NeurIPS), 2022 

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Private Isotonic Regression


Oct 27, 2022
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

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* Neural Information Processing Systems (NeurIPS), 2022 

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Algorithms with More Granular Differential Privacy Guarantees


Sep 08, 2022
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thomas Steinke

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Faster Privacy Accounting via Evolving Discretization


Jul 10, 2022
Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

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* Appeared in International Conference on Machine Learning (ICML) 2022 

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Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions


Jul 10, 2022
Vadym Doroshenko, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

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* Appeared in Privacy Enhancing Technologies Symposium (PETS) 2022 

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User-Level Private Learning via Correlated Sampling


Oct 21, 2021
Badih Ghazi, Ravi Kumar, Pasin Manurangsi

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* To appear in NeurIPS 2021 

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Large-Scale Differentially Private BERT


Aug 03, 2021
Rohan Anil, Badih Ghazi, Vineet Gupta, Ravi Kumar, Pasin Manurangsi

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* 12 pages, 6 figures 

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Locally Private k-Means in One Round


May 15, 2021
Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi

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* 35 pages. To appear in ICML'21 

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