| Fine-tuning large language models with user-level differential privacy Z Charles, A Ganesh, R McKenna, HB McMahan, N Mitchell, K Pillutla, ... arXiv preprint arXiv:2407.07737, 2024 | 52 | 2024 |
| Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins D Devaurs, DA Antunes, S Hall-Swan, N Mitchell, M Moll, G Lizée, ... BMC molecular and cell biology 20 (1), 42, 2019 | 47 | 2019 |
| Towards federated foundation models: Scalable dataset pipelines for group-structured learning Z Charles, N Mitchell, K Pillutla, M Reneer, Z Garrett Advances in Neural Information Processing Systems 36, 32299-32327, 2023 | 35 | 2023 |
| Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice AF Cooper, CA Choquette-Choo, M Bogen, M Jagielski, K Filippova, ... arXiv preprint arXiv:2412.06966, 2024 | 33 | 2024 |
| Optimizing the communication-accuracy trade-off in federated learning with rate-distortion theory N Mitchell, J Ballé, Z Charles, J Konečný arXiv preprint arXiv:2201.02664, 2022 | 33 | 2022 |
| Jaxpruner: A concise library for sparsity research JH Lee, W Park, NE Mitchell, J Pilault, JSO Ceron, HB Kim, N Lee, ... Conference on Parsimony and Learning, 515-528, 2024 | 16 | 2024 |
| danah boyd, Jennifer Wortman Vaughan, Miles Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna Wallach, Nicolas Papernot, and Katherine Lee. 2024. Machine … AF Cooper, CA Choquette-Choo, M Bogen, M Jagielski, K Filippova, ... arXiv preprint arXiv:2412.06966, 0 | 13 | |
| Redirection for Erasing Memory (REM): Towards a universal unlearning method for corrupted data S Schoepf, MC Mozer, NE Mitchell, A Brintrup, G Kaissis, P Kairouz, ... arXiv preprint arXiv:2505.17730, 2025 | 9 | 2025 |
| Leveraging function space aggregation for federated learning at scale N Dhawan, N Mitchell, Z Charles, Z Garrett, GK Dziugaite arXiv preprint arXiv:2311.10291, 2023 | 8 | 2023 |
| danah boyd, Jennifer Wortman Vaughan, Miles Brundage, David Bau, Seth Neel, Abigail Z AF Cooper, CA Choquette-Choo, M Bogen, M Jagielski, K Filippova, ... Jacobs, Andreas Terzis, Hanna M. Wallach, Nicolas Papernot, and Katherine …, 2024 | 7 | 2024 |
| Drjax: Scalable and differentiable mapreduce primitives in jax K Rush, Z Charles, Z Garrett, S Augenstein, N Mitchell arXiv preprint arXiv:2403.07128, 2024 | 7 | 2024 |
| How federated learning protects privacy N Mitchell, A Pearce URL https://pair. withgoogle. com/explorables/federated-learning, 2022 | 3 | 2022 |
| Examining data compartmentalization for AI governance NE Mitchell, E Triantafillou, P Kairouz NeurIPS 2024 Workshop on Regulatable ML, 2024 | 1 | 2024 |
| Learning with User-Level Differential Privacy Under Fixed Compute Budgets Z Charles, A Ganesh, R McKenna, HB McMahan, N Mitchell, K Pillutla, ... 2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 901-920, 2025 | | 2025 |
| Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice A Feder Cooper, CA Choquette-Choo, M Bogen, M Jagielski, K Filippova, ... arXiv e-prints, arXiv: 2412.06966, 2024 | | 2024 |
| Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research AF Cooper, CA Choquette-Choo, M Bogen, K Klyman, M Jagielski, ... The Thirty-Ninth Annual Conference on Neural Information Processing Systems …, 2024 | | 2024 |
| A Rate--Distortion View on Model Updates NE Mitchell, J Ballé, Z Charles, J Konečný | | 2023 |
| Machine Learning-Based Prediction of Sites of Metabolism in Drugs: Exploring Feature Extraction Methods on Molecular Graphs NE Mitchell Rice University, 2020 | | 2020 |
Zachary CharlesResearch Scientist, GoogleVerified email at google.com
