Research
(* indicates equal contribution.)
Private Fine-tuning of Large Language Models with Zeroth-order Optimization, Arxiv 2024
Xinyu Tang*, Ashwinee Panda*, Milad Nasr, Saeed Mahloujifar, Prateek Mittal
Paper
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation, ICLR 2024
Xinyu Tang, Richard Shin, Huseyin A. Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Robert Sim
Paper / Code
Differentially Private Image Classification by Learning Priors from Random Processes, NeurIPS 2023 (Spotlight)
Xinyu Tang*, Ashwinee Panda*, Vikash Sehwag, Prateek Mittal
Paper / Code / Twitter
Effectively Using Public Data in Privacy Preserving Machine Learning, ICML 2023
Milad Nasr, Saeed Mahloujifar, Xinyu Tang, Prateek Mittal, Amir Houmansadr
Paper / Video
A New Linear Scaling Rule for Differentially Private Hyperparameter Optimization, Arxiv 2022
Ashwinee Panda*, Xinyu Tang*, Vikash Sehwag, Saeed Mahloujifar, Prateek Mittal
Paper / Code / Video
Machine Learning with Differentially Private Labels: Mechanisms and Frameworks, PETS 2022
Xinyu Tang, Milad Nasr, Saeed Mahloujifar, Virat Shejwalkar, Liwei Song, Amir Houmansadr, Prateek Mittal
Paper / Code / Video
Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture, USENIX Security 2022
Xinyu Tang, Saeed Mahloujifar, Liwei Song, Virat Shejwalkar, Milad Nasr, Amir Houmansadr, Prateek Mittal
Paper / Code / Video
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