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A Field Guide to Federated Optimization


Jul 14, 2021
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Aguera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecny, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtarik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu


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Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection


Jun 15, 2021
Tuo Zhang, Chaoyang He, Tianhao Ma, Mark Ma, Salman Avestimehr


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SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks


Jun 04, 2021
Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr

* Three co-1st authors have equal contribution (alphabetical order) 

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Lightweight Image Super-Resolution with Hierarchical and Differentiable Neural Architecture Search


May 09, 2021
Han Huang, Li Shen, Chaoyang He, Weisheng Dong, Haozhi Huang, Guangming Shi


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FedNLP: A Research Platform for Federated Learning in Natural Language Processing


Apr 18, 2021
Bill Yuchen Lin, Chaoyang He, Zihang Zeng, Hulin Wang, Yufen Huang, Mahdi Soltanolkotabi, Xiang Ren, Salman Avestimehr

* Github link: https://github.com/FedML-AI/FedNLP 

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FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks


Apr 14, 2021
Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Yu Rong, Peilin Zhao, Junzhou Huang, Murali Annavaram, Salman Avestimehr

* The first three authors contribute equally. Our shorter versions are accepted to ICLR 2021 Workshop on Distributed and Private Machine Learning(DPML) and MLSys 2021 GNNSys Workshop on Graph Neural Networks and Systems 

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PipeTransformer: Automated Elastic Pipelining for Distributed Training of Transformers


Feb 12, 2021
Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr


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Group Knowledge Transfer: Collaborative Training of Large CNNs on the Edge


Jul 30, 2020
Chaoyang He, Murali Annavaram, Salman Avestimehr

* This paper attempts to address one of the core problems of federated learning: training deep neural networks in resource-constrained edge devices 

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FedML: A Research Library and Benchmark for Federated Machine Learning


Jul 27, 2020
Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram, Salman Avestimehr

* We maintain the source code, documents, and user community at https://fedml.ai 

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FedNAS: Federated Deep Learning via Neural Architecture Search


Apr 18, 2020
Chaoyang He, Murali Annavaram, Salman Avestimehr

* accepted to CVPR 2020 workshop on neural architecture search and beyond for representation learning 

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MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation


Mar 27, 2020
Chaoyang He, Haishan Ye, Li Shen, Tong Zhang

* This paper is published in CVPR 2020 (IEEE/CVF Conference on Computer Vision and Pattern Recognition 2020) 

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Advances and Open Problems in Federated Learning


Dec 10, 2019
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Keith Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaid Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konečný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao


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Central Server Free Federated Learning over Single-sided Trust Social Networks


Oct 11, 2019
Chaoyang He, Conghui Tan, Hanlin Tang, Shuang Qiu, Ji Liu


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Adversarial Representation Learning on Large-Scale Bipartite Graphs


Jun 27, 2019
Chaoyang He, Tian Xie, Yu Rong, Wenbing Huang, Junzhou Huang, Xiang Ren, Cyrus Shahabi

* 15 pages. Submitted to NeurIPS 2019 (Thirty-third Conference on Neural Information Processing Systems) 

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