21 citations · 34 across the 8 of their papers we have counts for
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cs.LG2024★ 1 cited
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs
Charlie Hou, Akshat Shrivastava, Hongyuan Zhan +5
On-device training is currently the most common approach for training machine learning (ML) models on private, distributed user data. Despite this, on-device training has several d…
cs.LG2024
Characterizing the Training Dynamics of Private Fine-tuning with Langevin diffusion
Shuqi Ke, Charlie Hou, Sewoong Oh +1
We show that differentially private full fine-tuning (DP-FFT) can distort pre-trained backbone features based on both theoretical and empirical results. We identify the cause of th…