Training Large-Vocabulary Neural Language Model by Private Federated Learning for Resource-Constrained Devices
Machine Learning Research at Apple
DECEMBER 17, 2023
*= Equal Contributors Federated Learning (FL) is a technique to train models using data distributed across devices. Differential Privacy (DP) provides a formal privacy guarantee for sensitive data. Our goal is to train a large neural network language model (NNLM) on compute-constrained devices while preserving privacy using FL and DP. However, the DP-noise introduced to the model increases as the model size grows, which often prevents convergence.
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