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Blaise Agüera y Arcas

Name: dblp XML data dump
Creator: Schloss Dagstuhl - Leibniz Center for Informatics
Published: 1993
License: https://creativecommons.org/publicdomain/zero/1.0/
Keywords: dblp, XML, computer science, scholarly publications, metadata

◀ ▶ joint publications with H. Brendan McMahan

> Home > Persons > Blaise Agüera y Arcas

Publications

2022
[i9]
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  - journals/corr/abs-2208-09432
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Zachary Charles, Kallista A. Bonawitz, Stanislav Chiknavaryan, Brendan McMahan, Blaise Agüera y Arcas:
Federated Select: A Primitive for Communication- and Memory-Efficient Federated Learning. CoRR abs/2208.09432 (2022)
2021
[i6]
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  - journals/corr/abs-2107-06917
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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)
2020
[c6]
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  - conf/iclr/AugensteinMRRKC20
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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
2019
[i3]
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  - journals/corr/abs-1911-06679
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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 abs/1911.06679 (2019)
2017
[c4]
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  - conf/aistats/McMahanMRHA17
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Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, Blaise Agüera y Arcas:
Communication-Efficient Learning of Deep Networks from Decentralized Data. AISTATS 2017: 1273-1282
2016
[i1]
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  - journals/corr/McMahanMRA16
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H. Brendan McMahan, Eider Moore, Daniel Ramage, Blaise Agüera y Arcas:
Federated Learning of Deep Networks using Model Averaging. CoRR abs/1602.05629 (2016)

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