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The Sample Complexity of Distribution-Free Parity Learning in the Robust Shuffle Model


Mar 29, 2021
Kobbi Nissim, Chao Yan


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On the Round Complexity of the Shuffle Model


Sep 28, 2020
Amos Beimel, Iftach Haitner, Kobbi Nissim, Uri Stemmer


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The power of synergy in differential privacy: Combining a small curator with local randomizers


Dec 20, 2019
Amos Beimel, Aleksandra Korolova, Kobbi Nissim, Or Sheffet, Uri Stemmer


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The power of synergy in differential privacy:Combining a small curator with local randomizers


Dec 18, 2019
Amos Beimel, Aleksandra Korolova, Kobbi Nissim, Or Sheffet, Uri Stemmer


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Differentially Private Summation with Multi-Message Shuffling


Jun 24, 2019
Borja Balle, James Bell, Adria Gascon, Kobbi Nissim


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The Privacy Blanket of the Shuffle Model


Mar 07, 2019
Borja Balle, James Bell, Adria Gascon, Kobbi Nissim


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Private Center Points and Learning of Halfspaces


Feb 27, 2019
Amos Beimel, Shay Moran, Kobbi Nissim, Uri Stemmer

* 14 pages 

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The Limits of Post-Selection Generalization


Jun 15, 2018
Kobbi Nissim, Adam Smith, Thomas Steinke, Uri Stemmer, Jonathan Ullman


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Locating a Small Cluster Privately


Mar 13, 2017
Kobbi Nissim, Uri Stemmer, Salil Vadhan


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Concentration Bounds for High Sensitivity Functions Through Differential Privacy


Mar 06, 2017
Kobbi Nissim, Uri Stemmer


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Private Incremental Regression


Jan 04, 2017
Shiva Prasad Kasiviswanathan, Kobbi Nissim, Hongxia Jin

* To appear in PODS 2017 

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Adaptive Learning with Robust Generalization Guarantees


Jun 02, 2016
Rachel Cummings, Katrina Ligett, Kobbi Nissim, Aaron Roth, Zhiwei Steven Wu


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Simultaneous Private Learning of Multiple Concepts


Nov 27, 2015
Mark Bun, Kobbi Nissim, Uri Stemmer

* 29 pages. To appear in ITCS '16 

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On the Generalization Properties of Differential Privacy


Nov 10, 2015
Kobbi Nissim, Uri Stemmer

* This paper was merged with another manuscript and is now subsumed by arXiv:1511.02513 

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Algorithmic Stability for Adaptive Data Analysis


Nov 08, 2015
Raef Bassily, Kobbi Nissim, Adam Smith, Thomas Steinke, Uri Stemmer, Jonathan Ullman

* This work unifies and subsumes the two arXiv manuscripts arXiv:1503.04843 and arXiv:1504.05800 

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Learning Privately with Labeled and Unlabeled Examples


Jul 01, 2015
Amos Beimel, Kobbi Nissim, Uri Stemmer


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Differentially Private Release and Learning of Threshold Functions


Apr 28, 2015
Mark Bun, Kobbi Nissim, Uri Stemmer, Salil Vadhan

* 43 pages 

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Private Learning and Sanitization: Pure vs. Approximate Differential Privacy


Jul 10, 2014
Amos Beimel, Kobbi Nissim, Uri Stemmer


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Characterizing the Sample Complexity of Private Learners


Feb 10, 2014
Amos Beimel, Kobbi Nissim, Uri Stemmer


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What Can We Learn Privately?


Feb 19, 2010
Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi Nissim, Sofya Raskhodnikova, Adam Smith

* SIAM Journal of Computing 40(3) (2011) 793-826 
* 35 pages, 2 figures 

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