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We study the fundamental problem of frequency estimation under both privacy and communication constraints, where the data is distributed among $k$ parties.
The probabilistic method
Jiří Matoušek and Jan Vondrák · 2001
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Finding frequent items in data streams
Moses Charikar, Kevin Chen, and Martin Farach-Colton · 2002
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An improved data stream summary: the count-min sketch and its applications
Graham Cormode and Shan Muthukrishnan · 2005
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Our data, ourselves: Privacy via distributed noise generation
Cynthia Dwork, Krishnaram Kenthapadi, Frank McSherry, Ilya Mironov, and Moni Naor · 2006
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Distributed private data analysis: Simultaneously solving how and what
Amos Beimel, Kobbi Nissim, and Eran Omri · 2008
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Methods for finding frequent items in data streams
Graham Cormode and Marios Hadjieleftheriou · 2010
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Differential privacy under continual observation
Cynthia Dwork, Moni Naor, Toniann Pitassi, and Guy N Rothblum · 2010
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Multiparty differential privacy via aggregation of locally trained classifiers
Manas Pathak, Shantanu Rane, and Bhiksha Raj · 2010
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Private and continual release of statistics
T-H Hubert Chan, Elaine Shi, and Dawn Song · 2011
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Algorithms for distributed functional monitoring
Graham Cormode, Senthilmurugan Muthukrishnan, and Ke Yi · 2011
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Differentially private continual monitoring of heavy hitters from distributed streams
T-H Hubert Chan, Mingfei Li, Elaine Shi, and Wenchang Xu · 2012
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Optimal lower bound for differentially private multi-party aggregation
TH Hubert Chan, Elaine Shi, and Dawn Song · 2012
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Continuous sampling from distributed streams
Graham Cormode, Senthilmurugan Muthukrishnan, Ke Yi, and Qin Zhang · 2012
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Universally utility-maximizing privacy mechanisms
Arpita Ghosh, Tim Roughgarden, and Mukund Sundararajan · 2012
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Quantiles over data streams: an experimental study
Lu Wang, Ge Luo, Ke Yi, and Graham Cormode · 2013
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The algorithmic foundations of differential privacy
Cynthia Dwork, Aaron Roth, et al · 2014
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RAPPOR: randomized aggregatable privacy-preserving ordinal response
Úlfar Erlingsson, Vasyl Pihur, and Aleksandra Korolova · 2014
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Extremal mechanisms for local differential privacy
Peter Kairouz, Sewoong Oh, and Pramod Viswanath · 2014
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Local, private, efficient protocols for succinct histograms
Raef Bassily and Adam Smith · 2015
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Data stream algorithms
Amit Chakrabarti · 2015
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Learning privately from multiparty data
Jihun Hamm, Yingjun Cao, and Mikhail Belkin · 2016
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Hadamard response: Estimating distributions privately, efficiently, and with little communication
Jayadev Acharya, Ziteng Sun, and Huanyu Zhang · 2019
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The privacy blanket of the shuffle model
Borja Balle, James Bell, Adrià Gascón, and Kobbi Nissim · 2019
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Answering range queries under local differential privacy
Graham Cormode, Tejas Kulkarni, and Divesh Srivastava · 2019
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Amplification by shuffling: From local to central differential privacy via anonymity
Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, and Abhradeep Thakurta · 2019
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On the power of multiple anonymous messages
Badih Ghazi, Noah Golowich, Ravi Kumar, Rasmus Pagh, and Ameya Velingker · 2019
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Apple · 2017
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Practical locally private heavy hitters
Raef Bassily, Kobbi Nissim, Uri Stemmer, and Abhradeep Thakurta · 2017
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Collecting telemetry data privately
Bolin Ding, Janardhan Kulkarni, and Sergey Yekhanin · 2017
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The communication complexity of distributed epsilon-approximations
Zengfeng Huang and Ke Yi · 2017
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Distributed private data analysis: Lower bounds and practical constructions
Elaine Shi, T.-H Chan, Eleanor Rieffel, and Dawn Song · 2017
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The complexity of differential privacy
Salil Vadhan · 2017
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Peter Kairouz, H Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Keith Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, et al · 2019
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Sublinear space private algorithms under the sliding window model
Jalaj Upadhyay · 2019
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Practical locally private heavy hitters
Raef Bassily, Kobbi Nissim, Uri Stemmer, and Abhradeep Thakurta · 2020
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Breaking the communication-privacy-accuracy trilemma
Wei-Ning Chen, Peter Kairouz, and Ayfer Özgür · 2020
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Small Summaries for Big Data
Graham Cormode and Ke Yi · 2020
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Private counting from anonymous messages: Near-optimal accuracy with vanishing communication overhead
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, and Rasmus Pagh · 2020
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Teng Wang, Xuefeng Zhang, Jingyu Feng, and Xinyu Yang · 2020
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Local differential privacy and its applications: A comprehensive survey
Mengmeng Yang, Lingjuan Lyu, Jun Zhao, Tianqing Zhu, and Kwok-Yan Lam · 2020
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Lossless compression of efficient private local randomizers
Vitaly Feldman and Kunal Talwar · 2021
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