H. Brendan McMahan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
20
Venues
10
Active years
2003–2024
Best venue rank
A*
Where they publish
Papers
20 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2024 | FOCS | Efficient and Near-Optimal Noise Generation for Streaming Differential Privacy. | Krishnamurthy Dj Dvijotham, H. Brendan McMahan, Krishna Pillutla, Thomas Steinke, Abhradeep Thakurta |
| 2023 | ACL | Federated Learning of Gboard Language Models with Differential Privacy. | Zheng Xu, Yanxiang Zhang, Galen Andrew, Christopher A. Choquette-Choo, Peter Kairouz, H. Brendan McMahan, Jesse Rosenstock, Yuanbo Zhang |
| 2023 | CVPR | Learning to Generate Image Embeddings with User-Level Differential Privacy. | Zheng Xu, Maxwell D. Collins, Yuxiao Wang, Liviu Panait, Sewoong Oh, Sean Augenstein, Ting Liu, Florian Schroff, H. Brendan McMahan |
| 2020 | ICLR | Generative Models for Effective ML on Private, Decentralized Datasets. | Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Agera y Arcas |
| 2020 | ICML | Is Local SGD Better than Minibatch SGD? | Blake E. Woodworth, Kumar Kshitij Patel, Sebastian U. Stich, Zhen Dai, Brian Bullins, H. Brendan McMahan, Ohad Shamir, Nathan Srebro |
| 2018 | ICLR | Learning Differentially Private Recurrent Language Models. | H. Brendan McMahan, Daniel Ramage, Kunal Talwar, Li Zhang |
| 2017 | CCS | Practical Secure Aggregation for Privacy-Preserving Machine Learning. | Kallista A. Bonawitz, Vladimir Ivanov, Ben Kreuter, Antonio Marcedone, H. Brendan McMahan, Sarvar Patel, Daniel Ramage, Aaron Segal, Karn Seth |
| 2017 | ICML | Distributed Mean Estimation with Limited Communication. | Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan |
| 2016 | CCS | Deep Learning with Differential Privacy. | Martn Abadi, Andy Chu, Ian J. Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, Li Zhang |
| 2014 | COLT | Unconstrained Online Linear Learning in Hilbert Spaces: Minimax Algorithms and Normal Approximations. | H. Brendan McMahan, Francesco Orabona |
| 2013 | ICML | Large-Scale Learning with Less RAM via Randomization. | Daniel Golovin, D. Sculley, H. Brendan McMahan, Michael Young |
| 2013 | KDD | Ad click prediction: a view from the trenches. | H. Brendan McMahan, Gary Holt, David Sculley, Michael Young, Dietmar Ebner, Julian Grady, Lan Nie, Todd Phillips, Eugene Davydov, Daniel Golovin, Sharat Chikkerur, Dan Liu, Martin Wattenberg, Arnar Mar Hrafnkelsson, Tom Boulos, Jeremy Kubica |
| 2010 | COLT | Adaptive Bound Optimization for Online Convex Optimization. | H. Brendan McMahan, Matthew J. Streeter |
| 2009 | COLT | Tighter Bounds for Multi-Armed Bandits with Expert Advice. | H. Brendan McMahan, Matthew J. Streeter |
| 2007 | AAAI | A Unification of Extensive-Form Games and Markov Decision Processes. | H. Brendan McMahan, Geoffrey J. Gordon |
| 2007 | ICML | Efficiently computing minimax expected-size confidence regions. | Brent Bryan, H. Brendan McMahan, Chad M. Schafer, Jeff G. Schneider |
| 2005 | ICML | Bounded real-time dynamic programming: RTDP with monotone upper bounds and performance guarantees. | H. Brendan McMahan, Maxim Likhachev, Geoffrey J. Gordon |
| 2005 | SODA | Online convex optimization in the bandit setting: gradient descent without a gradient. | Abraham Flaxman, Adam Tauman Kalai, H. Brendan McMahan |
| 2004 | COLT | Online Geometric Optimization in the Bandit Setting Against an Adaptive Adversary. | H. Brendan McMahan, Avrim Blum |
| 2003 | ICML | Planning in the Presence of Cost Functions Controlled by an Adversary. | H. Brendan McMahan, Geoffrey J. Gordon, Avrim Blum |