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We describe the design of our federated task processing system.
Binary codes capable of correcting deletions, insertions and reversals
V. I. Levenshtein · 1966
Earlier work this paper cites.
Class-based n-gram models of natural language
Peter F. Brown, Peter V. deSouza, Robert L. Mercer, Vincent J. Della Pietra, and Jenifer C. Lai · 1992
Earlier work this paper cites.
Large vocabulary decoding and confidence estimation using word posterior probabilitie
G. Evermann and P.C. Woodland · 2000
Earlier work this paper cites.
Confidence measures for large vocabulary continuous speech recognition
F. Wessel, R. Schluter, K. Macherey, and H. Ney · 2001
Earlier work this paper cites.
Improving utterance verification using a smoothed naive bayes model
Alberto Sanchís, Alfons Juan, and Enrique Vidal · 2003
Earlier work this paper cites.
Confidence measures for speech recognition: A survey
Hui Jiang · 2005
Earlier work this paper cites.
Combining information sources for confidence estimation with crf models
Matthew Stephen Seigel and Philip Charles Woodland · 2011
Earlier work this paper cites.
Learning to learn, 2012
S. Thrun and L. Pratt · 2012
Earlier work this paper cites.
Dynamic grammars with lookahead composition for wfst-based speech recognition
Josef R. Novak, Nobuaki Minematsu, and Keikichi Hirose · 2012
Earlier work this paper cites.
The algorithmic foundations of differential privacy
Cynthia Dwork and Aaron Roth · 2014
Earlier work this paper cites.
Accurate client-server based speech recognition keeping personal data on the client
M. Georges, S. Kanthak, and D. Klakow · 2014
Earlier work this paper cites.
Model inversion attacks that exploit confidence information and basic countermeasures
Matt Fredrikson, S. Jha, and T. Ristenpart · 2015
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Federated learning of deep networks using model averaging
H. Brendan McMahan, Eider Moore, Daniel Ramage, and Blaise Agüera y Arcas · 2016
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Federated optimization: Distributed machine learning for on-device intelligence
Jakub Konecný, 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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Practical secure aggregation for federated learning on user-held data
Privacy preserving encrypted phonetic search of speech data
C. Glackin, G. Chollet, N. Dugan, N. Cannings, J. Wall, S. Tahir, I. G. Ray, and M. Rajarajan · 2017
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On first-order meta-learning algorithms
Alex Nichol, Joshua Achiam, and John Schulman · 2018
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DJAM: distributed jacobi asynchronous method for learning personal models
Inês Almeida and João Xavier · 2018
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Inference attacks against collaborative learning
Luca Melis, Congzheng Song, Emiliano De Cristofaro, and Vitaly Shmatikov · 2018
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Towards federated learning at scale: System design, 2019
Keith Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloe Kiddon, Jakub Konecný, Stefano Mazzocchi, H. Brendan McMahan, Timon Van Overveldt, David Petrou, Daniel Ramage, and Jason Roselander · 2019
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Keith Bonawitz, Vladimir Ivanov, Ben Kreuter, Antonio Marcedone, H. Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, and Karn Seth · 2016
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Decentralized collaborative learning of personalized models over networks
Paul Vanhaesebrouck, Aurélien Bellet, and Marc Tommasi · 2016
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Personalized speech recognition on mobile devices
Ian McGraw, Rohit Prabhavalkar, Raziel Alvarez, Montse Gonzalez Arenas, Kanishka Rao, David Rybach, Ouais Alsharif, Hasim Sak, Alexander Gruenstein, Françoise Beaufays, and Carolina Parada · 2016
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Method for supporting dynamic grammars in wfst-based asr, November 22 2016
M. Paulik and R. Huang · 2016
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Virginia Smith, Chao-Kai Chiang, Maziar Sanjabi, and Ameet Talwalkar · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
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Fast and differentially private algorithms for decentralized collaborative machine learning
Aurélien Bellet, Rachid Guerraoui, Mahsa Taziki, and Marc Tommasi · 2017
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Federated learning: Challenges, methods, and future directions
Tian Li, Anit Kumar Sahu, Ameet Talwalkar, and Virginia Smith · 2019
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Advances and open problems in federated learning
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, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, 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, and Sen Zhao · 2019
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Variational federated multi-task learning
Luca Corinzia and Joachim M. Buhmann · 2019
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Improving federated learning personalization via model agnostic meta learning
Yihan Jiang, Jakub Konecný, Keith Rush, and Sreeram Kannan · 2019
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Protection against reconstruction and its applications in private federated learning, 2019
Abhishek Bhowmick, John Duchi, Julien Freudiger, Gaurav Kapoor, and Ryan Rogers · 2019
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Improving on-device speaker verification using federated learning with privacy
Filip Granqvist, Matt Seigel, Rogier Dalen, Áine Cahill, Stephen Shum, and Matthias Paulik · 2020
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