Federated Learning of Gboard Language Models with Differential Privacy

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Federated Learning of Gboard Language Models with Differential Privacy

29 May 2023

Christopher A. Choquette-Choo

Jesse Rosenstock

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Papers citing "Federated Learning of Gboard Language Models with Differential Privacy"

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Title
Private Federated Learning with Autotuned Compression Enayat Ullah Christopher A. Choquette-Choo Peter Kairouz Sewoong Oh FedML 81 8 0 20 Jul 2023
Private Federated Learning in Gboard Yuanbo Zhang Daniel Ramage Zheng Xu Yanxiang Zhang Shumin Zhai Peter Kairouz FedML 105 7 0 26 Jun 2023
(Amplified) Banded Matrix Factorization: A unified approach to private training Christopher A. Choquette-Choo Arun Ganesh Ryan McKenna H. B. McMahan Keith Rush Abhradeep Thakurta Zheng Xu FedML 111 41 0 13 Jun 2023
Information Flow Control in Machine Learning through Modular Model Architecture Trishita Tiwari Suchin Gururangan Chuan Guo Weizhe Hua Sanjay Kariyappa Udit Gupta Wenjie Xiong Kiwan Maeng Hsien-Hsin S. Lee G. E. Suh 75 6 0 05 Jun 2023
Selective Pre-training for Private Fine-tuning Da Yu Sivakanth Gopi Janardhan Kulkarni Zinan Lin Saurabh Naik Tomasz Religa Jian Yin Huishuai Zhang 94 19 0 23 May 2023
Can Public Large Language Models Help Private Cross-device Federated Learning? Wei Ping Yibo Jacky Zhang Yuan Cao Yue Liu H. B. McMahan Sewoong Oh Zheng Xu Manzil Zaheer FedML 117 40 0 20 May 2023
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy Natalia Ponomareva Hussein Hazimeh Alexey Kurakin Zheng Xu Carson E. Denison H. B. McMahan Sergei Vassilvitskii Steve Chien Abhradeep Thakurta 156 183 0 01 Mar 2023
On the Convergence of Federated Averaging with Cyclic Client Participation Yae Jee Cho Pranay Sharma Gauri Joshi Zheng Xu Satyen Kale Tong Zhang FedML 112 33 0 06 Feb 2023
One-shot Empirical Privacy Estimation for Federated Learning Galen Andrew Peter Kairouz Sewoong Oh Alina Oprea H. B. McMahan Vinith Suriyakumar FedML 174 36 0 06 Feb 2023
Differentially Private Natural Language Models: Recent Advances and Future Directions Lijie Hu Ivan Habernal Lei Shen Di Wang AAML 98 19 0 22 Jan 2023
PiPar: Pipeline Parallelism for Collaborative Machine Learning Zihan Zhang Philip Rodgers Peter Kilpatrick I. Spence Blesson Varghese FedML 84 3 0 01 Dec 2022