Keith Rush - RankMe

23 papers A* 2B 1Journal 18Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Global Convergence of Multiplicative Updates for the Matrix Mechanism: A Collaborative Proof with Gemini 3. CoRR Keith Rush
2025	J	`jnl`	Communication-Efficient Language Model Training Scales Reliably and Robustly: Scaling Laws for DiLoCo. CoRR Zachary Charles, Gabriel Teston, Lucio Dery, Keith Rush, Nova Fallen, Zachary Garrett, Arthur Szlam, Arthur Douillard
2025	J	`jnl`	Correlated Noise Mechanisms for Differentially Private Learning. CoRR Krishna Pillutla, Jalaj Upadhyay, Christopher A. Choquette-Choo, Krishnamurthy Dvijotham, Arun Ganesh, Monika Henzinger, Jonathan Katz, Ryan McKenna, H. Brendan McMahan, Keith Rush, Thomas Steinke, Abhradeep Thakurta
2025	—	`conf`	Learning with User-Level Differential Privacy Under Fixed Compute Budgets. SaTML Zachary Charles, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, Nicole Mitchell, Krishna Pillutla, Keith Rush
2025	J	`jnl`	Streaming DiLoCo with overlapping communication: Towards a Distributed Free Lunch. CoRR Arthur Douillard, Yanislav Donchev, Keith Rush, Satyen Kale, Zachary Charles, Zachary Garrett, Gabriel Teston, Dave Lacey, Ross McIlroy, Jiajun Shen, Alexandre Ramé, Arthur Szlam, Marc'Aurelio Ranzato, Paul Barham
2024	J	`jnl`	Cascade-Aware Training of Language Models. CoRR Congchao Wang, Sean Augenstein, Keith Rush, Wittawat Jitkrittum, Harikrishna Narasimhan, Ankit Singh Rawat, Aditya Krishna Menon, Alec Go
2024	J	`jnl`	FAX: Scalable and Differentiable Federated Primitives in JAX. CoRR Keith Rush, Zachary Charles, Zachary Garrett
2024	J	`jnl`	Federated Automatic Differentiation. J. Mach. Learn. Res. Keith Rush, Zachary Charles, Zachary Garrett
2024	J	`jnl`	Fine-Tuning Large Language Models with User-Level Differential Privacy. CoRR Zachary Charles, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, Nicole Mitchell, Krishna Pillutla, Keith Rush
2023	J	`jnl`	(Amplified) Banded Matrix Factorization: A unified approach to private training. CoRR Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, Keith Rush, Abhradeep Guha Thakurta, Zheng Xu
2023	J	`jnl`	Convergence of Gradient Descent with Linearly Correlated Noise and Applications to Differentially Private Learning. CoRR Anastasia Koloskova, Ryan McKenna, Zachary Charles, Keith Rush, Brendan McMahan
2023	J	`jnl`	Federated Automatic Differentiation. CoRR Keith Rush, Zachary Charles, Zachary Garrett
2022	—	`conf`	Does Federated Dropout actually work? CVPR Workshops Gary Cheng, Zachary Charles, Zachary Garrett, Keith Rush
2022	B	`conf`	Iterated Vector Fields and Conservatism, with Applications to Federated Learning. ALT Zachary Charles, Keith Rush
2022	J	`jnl`	Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning. CoRR Christopher A. Choquette-Choo, H. Brendan McMahan, Keith Rush, Abhradeep Thakurta
2022	J	`jnl`	Private Online Prefix Sums via Optimal Matrix Factorizations. CoRR Brendan McMahan, Keith Rush, Abhradeep Guha Thakurta
2021	A*	`conf`	(Nearly) Dimension Independent Private ERM with AdaGrad Ratesvia Publicly Estimated Subspaces. COLT Peter Kairouz, Mónica Ribero Diaz, Keith Rush, Abhradeep Thakurta
2021	A*	`conf`	Adaptive Federated Optimization. ICLR Sashank J. Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konecný, Sanjiv Kumar, Hugh Brendan McMahan
2021	J	`jnl`	Federated Reconstruction: Partially Local Federated Learning. CoRR Karan Singhal, Hakim Sidahmed, Zachary Garrett, Shanshan Wu, Keith Rush, Sushant Prakash
2021	J	`jnl`	Iterated Vector Fields and Conservatism, with Applications to Federated Learning. CoRR Zachary Charles, Keith Rush
2020	J	`jnl`	Adaptive Federated Optimization. CoRR Sashank J. Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konecný, Sanjiv Kumar, H. Brendan McMahan
2020	J	`jnl`	Dimension Independence in Unconstrained Private ERM via Adaptive Preconditioning. CoRR Peter Kairouz, Mónica Ribero, Keith Rush, Abhradeep Thakurta
2019	J	`jnl`	Improving Federated Learning Personalization via Model Agnostic Meta Learning. CoRR Yihan Jiang, Jakub Konecný, Keith Rush, Sreeram Kannan