Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message. - Badih Ghazi; Ravi Kumar 001; Pasin Manurangsi; Rasmus Pagh; Amer Sinha (ICML, 2021)

Private Ad Modeling with DP-SGD. - Carson Denison; Badih Ghazi; Pritish Kamath; Ravi Kumar 001; Pasin Manurangsi; Krishna Giri Narra; Amer Sinha; Avinash V. Varadarajan; Chiyuan Zhang (AdKDD@KDD, 2023)

Sparsity-Preserving Differentially Private Training of Large Embedding Models. - Badih Ghazi; Yangsibo Huang; Pritish Kamath; Ravi Kumar 001; Pasin Manurangsi; Amer Sinha; Chiyuan Zhang (NeurIPS, 2023)

Training Differentially Private Ad Prediction Models With Semi-Sensitive Features. - Lynn Chua; Qiliang Cui; Badih Ghazi; Charlie Harrison; Pritish Kamath; Walid Krichene; Ravi Kumar 001; Pasin Manurangsi; Nicolas Mayoraz; Hema Venkata Krishna Giri Narra; Steffen Rendle; Amer Sinha; et al. (AdKDD@KDD, 2024)

How Private are DP-SGD Implementations? - Lynn Chua; Badih Ghazi; Pritish Kamath; Ravi Kumar 001; Pasin Manurangsi; Amer Sinha; Chiyuan Zhang (ICML, 2024)

Scalable DP-SGD: Shuffling vs. Poisson Subsampling. - Lynn Chua; Badih Ghazi; Pritish Kamath; Ravi Kumar 001; Pasin Manurangsi; Amer Sinha; Chiyuan Zhang (NeurIPS, 2024)

Training Differentially Private Ad Prediction Models with Semi-Sensitive Features. - Lynn Chua; Qiliang Cui; Badih Ghazi; Charlie Harrison; Pritish Kamath; Walid Krichene; Ravi Kumar 001; Pasin Manurangsi; Krishna Giri Narra; Amer Sinha; Avinash V. Varadarajan; Chiyuan Zhang (CoRR, 2024)

How Private is DP-SGD? - Lynn Chua; Badih Ghazi; Pritish Kamath; Ravi Kumar 001; Pasin Manurangsi; Amer Sinha; Chiyuan Zhang (CoRR, 2024)

Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning. - Lynn Chua; Badih Ghazi; Yangsibo Huang; Pritish Kamath; Daogao Liu; Pasin Manurangsi; Amer Sinha; Chiyuan Zhang (CoRR, 2024)

Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models. - Lynn Chua; Badih Ghazi; Yangsibo Huang; Pritish Kamath; Ravi Kumar 001; Pasin Manurangsi; Amer Sinha; Chulin Xie; Chiyuan Zhang (CoRR, 2024)

Balls-and-Bins Sampling for DP-SGD. - Lynn Chua; Badih Ghazi; Charlie Harrison; Pritish Kamath; Ravi Kumar 001; Ethan Leeman; Pasin Manurangsi; Amer Sinha; Chiyuan Zhang (AISTATS, 2025)

Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy. - Yangsibo Huang; Daogao Liu; Lynn Chua; Badih Ghazi; Pritish Kamath; Ravi Kumar 001; Pasin Manurangsi; Milad Nasr; Amer Sinha; Chiyuan Zhang (ICLR, 2025)

Scaling Laws for Differentially Private Language Models. - Ryan McKenna; Yangsibo Huang; Amer Sinha; Borja Balle; Zachary Charles; Christopher A. Choquette-Choo; Badih Ghazi; Georgios Kaissis; Ravi Kumar 001; Ruibo Liu; Da Yu; Chiyuan Zhang (CoRR, 2025)