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Recent advances in neural network based language models lead to successful deployments of such models, improving user experience in various applications.
k-anonymity: A model for protecting privacy
Latanya Sweeney · 2002
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A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Jauvin · 2003
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, and Melanie Subbiah · 2005
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Power laws, Pareto distributions and Zipf’s law
M.E.J. Newman · 2005
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Recurrent neural network based language model
Tomáš Mikolov, Martin Karafiát, Lukáš Burget, Jan “Honza” Černocký, and Sanjeev Khudanpur · 2010
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Differential privacy
Cynthia Dwork · 2011
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LSTM neural networks for language modeling
Martin Sundermeyer, Ralf Schlüter, and Hermann Ney · 2012
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When is memorization of irrelevant training data necessary for high-accuracy learning?
Gavin Brown, Mark Bun, Vitaly Feldman, Adam Smith, and Kunal Talwar · 2012
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Stochastic gradient descent with differentially private updates
Shuang Song, Kamalika Chaudhuri, and Anand D. Sarwate · 2013
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One billion word benchmark for measuring progress in statistical language modeling, 2013
Ciprian Chelba, Tomas Mikolov, Mike Schuster, Qi Ge, Thorsten Brants, Phillipp Koehn, and Tony Robinson · 2013
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Opinion 05/2014 on “Anonymisation Techniques”, 2014
Art. 29 WP · 2014
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Deep learning with differential privacy
Martin Abadi, Andy Chu, Ian Goodfellow, H Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang · 2016
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Conversational contextual cues: The case of personalization and history for response ranking, 2016
Rami Al-Rfou, Marc Pickett, Javier Snaider, Y.-H. Sung, Brian Strope, and Ray Kurzweil · 2016
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The Machine Intelligence Behind Gboard
Gboard · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, undefinedukasz Kaiser, and Illia Polosukhin · 2017
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Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher · 2017
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Understanding deep learning requires rethinking generalization
Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, and Oriol Vinyals · 2017
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Membership inference attacks against machine learning models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov · 2017
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SUBJECT: Write emails faster with Smart Compose in Gmail, 2018
Paul Lambert · 2018
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Deep contextualized word representations
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer · 2018
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Improving language understanding by generative pre-training, 2018
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder · 2018
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Learning differentially private recurrent language models
Brendan McMahan, Daniel Ramage, Kunal Talwar, and Li Zhang · 2018
Cited alongside, same era.
Privacy risk in machine learning: Analyzing the connection to overfitting
Auditing data provenance in text-generation models
Congzheng Song and Vitaly Shmatikov · 2019
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Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning
Milad Nasr, Reza Shokri, and Amir Houmansadr · 2019
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LOGAN: Membership inference attacks against generative models
Jamie Hayes, Luca Melis, George Danezis, and Emiliano De Cristofaro · 2019
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Demystifying the membership inference attack
Paul Irolla and Grégory Châtel · 2019
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White-box vs black-box: Bayes optimal strategies for membership inference
Alexandre Sablayrolles, Matthijs Douze, Cordelia Schmid, Yann Ollivier, and Herve Jegou · 2019
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Samuel Yeom, Irene Giacomelli, Matt Fredrikson, and Somesh Jha · 2018
Cited alongside, same era.
Understanding membership inferences on well-generalized learning models
Yunhui Long, Vincent Bindschaedler, Lei Wang, Diyue Bu, Xiaofeng Wang, Haixu Tang, Carl A. Gunter, and Kai Chen · 2018
Cited alongside, same era.
Towards demystifying membership inference attacks
Stacey Truex, Ling Liu, Mehmet Emre Gursoy, Lei Yu, and Wenqi Wei · 2018
Cited alongside, same era.
Ahmed Salem, Yang Zhang, Mathias Humbert, Mario Fritz, and Michael Backes · 2018
Cited alongside, same era.
The Secret Sharer: Evaluating and testing unintended memorization in neural networks
Nicholas Carlini, Chang Liu, Úlfar Erlingsson, Jernej Kos, and Dawn Song · 2019
Cited alongside, same era.
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, Timothy Sohn, and Yonghui Wu · 2019
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Cited alongside, same era.
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Keith Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, and et al · 2019
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Extracting training data from large language models
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, Alina Oprea, and Colin Raffel · 2020
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A 17-billion-parameter language model by Microsoft, 2020
Turing-NLG · 2020
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Guidance for regulation of artificial intelligence applications, 2019
White House Office of Science and Technology Policy (OSTP) · 2020
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Does learning require memorization? A short tale about a long tail
Vitaly Feldman · 2020
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Differentially private learning needs better features (or much more data)
Florian Tramèr and Dan Boneh · 2020
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Making the shoe fit: Architectures, initializations, and tuning for learning with privacy, 2020
Nicolas Papernot, Steve Chien, Shuang Song, Abhradeep Thakurta, and Ulfar Erlingsson · 2020
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Analyzing information leakage of updates to natural language models
Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Victor Rühle, Andrew Paverd, Olga Ohrimenko, Boris Köpf, and Marc Brockschmidt · 2020
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Membership inference attacks on sequence-to-sequence models: Is my data in your machine translation system?
Sorami Hisamoto, Matt Post, and Kevin Duh · 2020
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Stolen Memories: Leveraging model memorization for calibrated white-box membership inference
Klas Leino and Matt Fredrikson · 2020
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Label-only membership inference attacks
Christopher A. Choquette-Choo, Florian Tramer, Nicholas Carlini, and Nicolas Papernot · 2020
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ML Privacy Meter: Aiding regulatory compliance by quantifying the privacy risks of machine learning
Sasi Kumar Murakonda and Reza Shokri · 2020
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