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Large-Scale Differentially Private BERT


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

* 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

* 35 pages. To appear in ICML'21 

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On Deep Learning with Label Differential Privacy


Feb 11, 2021
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang

* 26 pages, 4 figures 

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On Avoiding the Union Bound When Answering Multiple Differentially Private Queries


Dec 16, 2020
Badih Ghazi, Ravi Kumar, Pasin Manurangsi

* 12 pages 

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Sample-efficient proper PAC learning with approximate differential privacy


Dec 07, 2020
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi

* 40 pages 

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Robust and Private Learning of Halfspaces


Nov 30, 2020
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen


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On Distributed Differential Privacy and Counting Distinct Elements


Sep 21, 2020
Lijie Chen, Badih Ghazi, Ravi Kumar, Pasin Manurangsi

* 68 pages, 4 algorithms 

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Differentially Private Clustering: Tight Approximation Ratios


Aug 18, 2020
Badih Ghazi, Ravi Kumar, Pasin Manurangsi

* 60 pages, 1 table 

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Near-tight closure bounds for Littlestone and threshold dimensions


Jul 07, 2020
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi

* 7 pages 

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Advances and Open Problems in Federated Learning


Dec 10, 2019
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Keith Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaid Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konečný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao


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Private Heavy Hitters and Range Queries in the Shuffled Model


Aug 29, 2019
Badih Ghazi, Noah Golowich, Ravi Kumar, Rasmus Pagh, Ameya Velingker

* 30 pages 

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Scalable and Differentially Private Distributed Aggregation in the Shuffled Model


Jun 19, 2019
Badih Ghazi, Rasmus Pagh, Ameya Velingker

* 17 pages, 1 figure, 1 table, 2 algorithms 

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Recursive Sketches for Modular Deep Learning


May 29, 2019
Badih Ghazi, Rina Panigrahy, Joshua R. Wang

* Published in ICML 2019 

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On the Power of Learning from $k$-Wise Queries


Feb 28, 2017
Vitaly Feldman, Badih Ghazi

* 32 pages, Appeared in Innovations in Theoretical Computer Science (ITCS) 2017 

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