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Recent works have shown that generative sequence models (e.g., language models) have a tendency to memorize rare or unique sequences in the training data.
On the momentum term in gradient descent learning algorithms
Ning Qian · 1999
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Revealing information while preserving privacy
Irit Dinur and Kobbi Nissim · 2003
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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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Our data, ourselves: Privacy via distributed noise generation
Cynthia Dwork, Krishnaram Kenthapadi, Frank Mcsherry, Ilya Mironov, and Moni Naor · 2006
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Calibrating noise to sensitivity in private data analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
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Resolving individuals contributing trace amounts of dna to highly complex mixtures using high-density snp genotyping microarrays
Nils Homer, Szabolcs Szelinger, Margot Redman, David Duggan, Waibhav Tembe, Jill Muehling, John V Pearson, Dietrich A Stephan, Stanley F Nelson, and David W Craig · 2008
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Genomic privacy and limits of individual detection in a pool
Sriram Sankararaman, Guillaume Obozinski, Michael I Jordan, and Eran Halperin · 2009
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Fingerprinting codes and the price of approximate differential privacy
Mark Bun, Jonathan Ullman, and Salil Vadhan · 2014
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Rappor: Randomized aggregatable privacy-preserving ordinal response
Úlfar Erlingsson, Vasyl Pihur, and Aleksandra Korolova · 2014
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Hasim Sak, Andrew W. Senior, and Françoise Beaufays · 2014
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Robust traceability from trace amounts
C. Dwork, A. Smith, T. Steinke, J. Ullman, and S. Vadhan · 2015
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Model inversion attacks that exploit confidence information and basic countermeasures
Matt Fredrikson, Somesh Jha, and Thomas Ristenpart · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Federated optimization: Distributed machine learning for on-device intelligence
Jakub Konečný, H. Brendan McMahan, Daniel Ramage, and Peter Richtárik · 2016
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Federated learning: Strategies for improving communication efficiency
Jakub Konecný, H. Brendan McMahan, Felix X. Yu, Peter Richtárik, Ananda Theertha Suresh, and Dave Bacon · 2016
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A methodology for formalizing model-inversion attacks
X. Wu, M. Fredrikson, S. Jha, and J. F. Naughton · 2016
Cited alongside, same era.
Learning with privacy at scale, 2017
Differential Privacy Team Apple · 2017
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Prochlo: Strong privacy for analytics in the crowd
Andrea Bittau, Úlfar Erlingsson, Petros Maniatis, Ilya Mironov, Ananth Raghunathan, David Lie, Mitch Rudominer, Ushasree Kode, Julien Tinnés, and Bernhard Seefeld · 2017
Cited alongside, same era.
Practical secure aggregation for privacy-preserving machine learning
Keith Bonawitz, Vladimir Ivanov, Ben Kreuter, Antonio Marcedone, H. Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, and Karn Seth · 2017
Cited alongside, same era.
Collecting telemetry data privately
Bolin Ding, Janardhan Kulkarni, and Sergey Yekhanin · 2017
Cited alongside, same era.
Rényi differential privacy
I. Mironov · 2017
Cited alongside, same era.
The Stack Overflow Data, 2018
Stack Overflow · 2018
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Towards federated learning at scale: System design
Keith Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloé Kiddon, Jakub Konecný, Stefano Mazzocchi, H. Brendan McMahan, Timon Van Overveldt, David Petrou, Daniel Ramage, and Jason Roselander · 2019
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Gmail smart compose: Real-time assisted writing
Mia Xu Chen, Benjamin N Lee, Gagan Bansal, Yuan Cao, Shuyuan Zhang, Justin Lu, Jackie Tsay, Yinan Wang, Andrew M Dai, Zhifeng Chen, et al · 2019
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Federated learning of n-gram language models
Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, and Michael Riley · 2019
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Introducing tensorflow federated, 2019
Alex Ingerman and Krzys Ostrowski · 2019
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Communication-efficient learning of deep networks from decentralized data
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Agüera y Arcas · 2017
Cited alongside, same era.
Federated learning: Collaborative machine learning without centralized training data
Brendan McMahan and Daniel Ramage · 2017
Cited alongside, same era.
Learning differentially private language models without losing accuracy
H. Brendan McMahan, Daniel Ramage, Kunal Talwar, and Li Zhang · 2017
Cited alongside, same era.
Membership inference attacks against machine learning models
R. Shokri, M. Stronati, C. Song, and V. Shmatikov · 2017
Cited alongside, same era.
The secret sharer: Measuring unintended neural network memorization & extracting secrets
Nicholas Carlini, Chang Liu, Jernej Kos, Úlfar Erlingsson, and Dawn Song · 2018
Cited alongside, same era.
Federated learning for mobile keyboard prediction
Andrew Hard, Kanishka Rao, Rajiv Mathews, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, and Daniel Ramage · 2018
Cited alongside, same era.
Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, and Ananda Theertha Suresh · 2019
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xkcd: Predictive models, 2019
Randall Munroe · 2019
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Federated learning for emoji prediction in a mobile keyboard, 2019
Swaroop Ramaswamy, Rajiv Mathews, Kanishka Rao, and Françoise Beaufays · 2019
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Auditing data provenance in text-generation models
Congzheng Song and Vitaly Shmatikov · 2019
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Differentially private learning with adaptive clipping
Om Thakkar, Galen Andrew, and H. Brendan McMahan · 2019
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Subsampled renyi differential privacy and analytical moments accountant
Yu-Xiang Wang, Borja Balle, and Shiva Prasad Kasiviswanathan · 2019
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Generative models for effective ML on private, decentralized datasets
Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, and Blaise Agüera y Arcas · 2020
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Encode, shuffle, analyze privacy revisited: Formalizations and empirical evaluation
Úlfar Erlingsson, Vitaly Feldman, Ilya Mironov, Ananth Raghunathan, Shuang Song, Kunal Talwar, and Abhradeep Thakurta · 2020
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Linkedin’s audience engagements api: A privacy preserving data analytics system at scale, 2020
Ryan Rogers, Subbu Subramaniam, Sean Peng, David Durfee, Seunghyun Lee, Santosh Kumar Kancha, Shraddha Sahay, and Parvez Ahammad · 2020
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