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Pritish Kamath
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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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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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Do More Negative Samples Necessarily Hurt in Contrastive Learning?


May 03, 2022
Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath

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* 16 pages 
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On the Power of Differentiable Learning versus PAC and SQ Learning


Aug 09, 2021
Emmanuel Abbe, Pritish Kamath, Eran Malach, Colin Sandon, Nathan Srebro

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Supervised Bayesian Specification Inference from Demonstrations


Jul 06, 2021
Ankit Shah, Pritish Kamath, Shen Li, Patrick Craven, Kevin Landers, Kevin Oden, Julie Shah

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Eluder Dimension and Generalized Rank


Apr 14, 2021
Gene Li, Pritish Kamath, Dylan J. Foster, Nathan Srebro

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* Technical Note 
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