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We show that a word-level recurrent neural network can predict emoji from text typed on a mobile keyboard.
Towards federated learning at scale: System design
Keith Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloe Kiddon, Jakub Konecny, Stefano Mazzocchi, H Brendan McMahan, et al. 2019 · 1902
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
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On the importance of initialization and momentum in deep learning
Ilya Sutskever, James Martens, George Dahl, and Geoffrey Hinton. 2013 · 2013
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Learning phrase representations using RNN encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 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 · 2016
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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 · 2017
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Natural language processing with small feed-forward networks
Jan A. Botha, Emily Pitler, Ji Ma, Anton Bakalov, Alex Salcianu, David I Weiss, Ryan T. McDonald, and Slav Petrov. 2017 · 2017
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Google Vizier: A Service for Black-Box Optimization
Daniel Golovin, Benjamin Solnik, Subhodeep Moitra, Greg Kochanski, John Elliot Karro, and D. Sculley, editors. 2017 · 2017
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Lstm: A search space odyssey
Klaus Greff, Rupesh Kumar Srivastava, Jan Koutnx00EDk, Bas R. Steunebrink, and Jx00FCrgen Schmidhuber. 2017 · 2017
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Transliterated mobile keyboard input via weighted finite-state transducers
Lars Hellsten, Brian Roark, Prasoon Goyal, Cyril Allauzen, Francoise Beaufays, Tom Ouyang, Michael Riley, and David Rybach. 2017 · 2017
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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 · 2017
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Using the output embedding to improve language models
Ofir Press and Lior Wolf. 2017 · 2017
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Federated learning for mobile keyboard prediction
Andrew Hard, Kanishka Rao, Rajiv Mathews, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, and Daniel Ramage. 2018 · 2018
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Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder. 2018 · 2018
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Learning differentially private recurrent language models
Brendan McMahan, Daniel Ramage, Kunal Talwar, and Li Zhang. 2018 · 2018
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Don’t decay the learning rate, increase the batch size
Samuel L. Smith, Pieter-Jan Kindermans, and Quoc V. Le. 2018 · 2018
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Applied federated learning: Improving google keyboard query suggestion
Timothy Yang, Galen Andrew, Hubert Eichner, Haicheng Sun, Wei Li, Nicholas Kong, Daniel Ramage, and Françoise Beaufays. 2018 · 2018
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Alec Radford, Rafal Józefowicz, and Ilya Sutskever. 2017 · 2017
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cpsgd: Communication-efficient and differentially-private distributed sgd
Naman Agarwal, Ananda Theertha Suresh, Felix Yu, Sanjiv Kumar, and Brendan McMahan. 2018 · 2018
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A fast, compact, accurate model for language identification of codemixed text
Yuan Zhang, Jason Riesa, Daniel Gillick, Anton Bakalov, Jason Baldridge, and David I Weiss. 2018 · 2018
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Tensorflow lite, “tensorflow’s solution for running machine learning models on mobile and embedded devices,”
TFLite · 2019
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