Sean Augenstein

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 12

Top Topics

Optimal Scheduling

Equivalence Class

Generative Model

Structural Learning

Top Venues

AAAI Spring Symposia

Publications

Andrew Hard, Antonious M. Girgis, Ehsan Amid, Sean Augenstein, Lara McConnaughey, Rajiv Mathews, Rohan Anil
Learning from straggler clients in federated learning. CoRR (2024)
Congchao Wang, Sean Augenstein, Keith Rush, Wittawat Jitkrittum, Harikrishna Narasimhan, Ankit Singh Rawat, Aditya Krishna Menon, Alec Go
Cascade-Aware Training of Language Models. CoRR (2024)
Zheng Xu, Maxwell D. Collins, Yuxiao Wang, Liviu Panait, Sewoong Oh, Sean Augenstein, Ting Liu, Florian Schroff, H. Brendan McMahan
Learning to Generate Image Embeddings with User-Level Differential Privacy. CVPR (2023)
Andrew Hard, Kurt Partridge, Neng Chen, Sean Augenstein, Aishanee Shah, Hyun Jin Park, Alex Park, Sara Ng, Jessica Nguyen, Ignacio Lopez-Moreno, Rajiv Mathews, Françoise Beaufays
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training. INTERSPEECH (2022)
Sean Augenstein, Andrew Hard, Lin Ning, Karan Singhal, Satyen Kale, Kurt Partridge, Rajiv Mathews
Mixed Federated Learning: Joint Decentralized and Centralized Learning. CoRR (2022)
Zheng Xu, Maxwell D. Collins, Yuxiao Wang, Liviu Panait, Sewoong Oh, Sean Augenstein, Ting Liu, Florian Schroff, H. Brendan McMahan
Learning to Generate Image Embeddings with User-level Differential Privacy. CoRR (2022)
Andrew Hard, Kurt Partridge, Neng Chen, Sean Augenstein, Aishanee Shah, Hyun Jin Park, Alex Park, Sara Ng, Jessica Nguyen, Ignacio Lopez-Moreno, Rajiv Mathews, Françoise Beaufays
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training. CoRR (2022)
Sean Augenstein, Andrew Hard, Kurt Partridge, Rajiv Mathews
Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shift. CoRR (2021)
Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Agüera y Arcas
Generative Models for Effective ML on Private, Decentralized Datasets. ICLR (2020)
Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Agüera y Arcas
Generative Models for Effective ML on Private, Decentralized Datasets. CoRR (2019)
Andrew Hard, Kanishka Rao, Rajiv Mathews, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, Daniel Ramage
Federated Learning for Mobile Keyboard Prediction. CoRR (2018)
Sean Augenstein, Alejandra Estanislao, Emmanuel Guere, Sean Blaes
Optimal Scheduling of a Constellation of Earth-Imaging Satellites, for Maximal Data Throughput and Efficient Human Management. ICAPS (2016)
Sean Augenstein
Optimal Scheduling of Earth-Imaging Satellites with Human Collaboration via Directed Acyclic Graphs. AAAI Spring Symposia (2014)
Jose Padial, Marcus Hammond, Sean Augenstein, Stephen M. Rock
Tumbling target reconstruction and pose estimation through fusion of monocular vision and sparse-pattern range data. MFI (2012)
Sean Augenstein, Stephen M. Rock
Improved frame-to-frame pose tracking during vision-only SLAM/SFM with a tumbling target. ICRA (2011)