Mitchell, Nicole Elyse

6 publications

NeurIPS 2025 Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Kevin Klyman, Matthew Jagielski, Katja Filippova, Ken Liu, Alexandra Chouldechova, Jamie Hayes, Yangsibo Huang, Eleni Triantafillou, Peter Kairouz, Nicole Elyse Mitchell, Niloofar Mireshghallah, Abigail Z. Jacobs, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Ilia Shumailov, Andreas Terzis, Solon Barocas, Jennifer Wortman Vaughan, Danah Boyd, Yejin Choi, Sanmi Koyejo, Fernando Delgado, Percy Liang, Daniel E. Ho, Pamela Samuelson, Miles Brundage, David Bau, Seth Neel, Hanna Wallach, Amy B. Cyphert, Mark Lemley, Nicolas Papernot, Katherine Lee

ICMLW 2024 DrJAX: Scalable and Differentiable MapReduce Primitives in JAX J Keith Rush, Zachary Charles, Zachary Garrett, Sean Augenstein, Nicole Elyse Mitchell

NeurIPSW 2024 Examining Data Compartmentalization for AI Governance Nicole Elyse Mitchell, Eleni Triantafillou, Peter Kairouz

ICMLW 2024 Fine-Tuning Large Language Models with User-Level Differential Privacy Zachary Charles, Arun Ganesh, Ryan McKenna, Hugh Brendan McMahan, Nicole Elyse Mitchell, Krishna Pillutla, J Keith Rush

CPAL 2024 Jaxpruner: A Concise Library for Sparsity Research Joo Hyung Lee, Wonpyo Park, Nicole Elyse Mitchell, Jonathan Pilault, Johan Samir Obando Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Woohyun Han, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J.C. Bik, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, Utku Evci

TMLR 2024 Leveraging Function Space Aggregation for Federated Learning at Scale Nikita Dhawan, Nicole Elyse Mitchell, Zachary Charles, Zachary Garrett, Gintare Karolina Dziugaite