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Andrew Hard
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2020 – today
- 2024
- [i7]Andrew Hard, Antonious M. Girgis, Ehsan Amid, Sean Augenstein, Lara McConnaughey, Rajiv Mathews, Rohan Anil:
Learning from straggler clients in federated learning. CoRR abs/2403.09086 (2024) - 2022
- [c3]Chen Zhu, Zheng Xu, Mingqing Chen, Jakub Konecný, Andrew Hard, Tom Goldstein:
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions. ICLR 2022 - [c2]Andrew Hard, Kurt Partridge, Neng Chen, Sean Augenstein, Aishanee Shah, Hyun Jin Park, Alex Park, Sara Ng, Jessica Nguyen, Ignacio López-Moreno, Rajiv Mathews, Françoise Beaufays:
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training. INTERSPEECH 2022: 76-80 - [i6]Andrew Hard, Kurt Partridge, Neng Chen, Sean Augenstein, Aishanee Shah, Hyun Jin Park, Alex Park, Sara Ng, Jessica Nguyen, Ignacio López-Moreno, Rajiv Mathews, Françoise Beaufays:
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training. CoRR abs/2204.06322 (2022) - [i5]Sean Augenstein, Andrew Hard, Lin Ning, Karan Singhal, Satyen Kale, Kurt Partridge, Rajiv Mathews:
Mixed Federated Learning: Joint Decentralized and Centralized Learning. CoRR abs/2205.13655 (2022) - 2021
- [i4]Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horváth
, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik
, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu:
A Field Guide to Federated Optimization. CoRR abs/2107.06917 (2021) - [i3]Sean Augenstein, Andrew Hard, Kurt Partridge, Rajiv Mathews:
Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shift. CoRR abs/2111.12150 (2021) - 2020
- [c1]Andrew Hard, Kurt Partridge, Cameron Nguyen, Niranjan Subrahmanya, Aishanee Shah, Pai Zhu, Ignacio López-Moreno, Rajiv Mathews:
Training Keyword Spotting Models on Non-IID Data with Federated Learning. INTERSPEECH 2020: 4343-4347 - [i2]Andrew Hard, Kurt Partridge, Cameron Nguyen, Niranjan Subrahmanya, Aishanee Shah, Pai Zhu, Ignacio López-Moreno, Rajiv Mathews:
Training Keyword Spotting Models on Non-IID Data with Federated Learning. CoRR abs/2005.10406 (2020)
2010 – 2019
- 2018
- [i1]Andrew Hard, Kanishka Rao, Rajiv Mathews, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, Daniel Ramage:
Federated Learning for Mobile Keyboard Prediction. CoRR abs/1811.03604 (2018)
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