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SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision


Oct 06, 2021
Chaoyang He, Zhengyu Yang, Erum Mushtaq, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr


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FairFed: Enabling Group Fairness in Federated Learning


Oct 02, 2021
Yahya H. Ezzeldin, Shen Yan, Chaoyang He, Emilio Ferrara, Salman Avestimehr


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LightSecAgg: Rethinking Secure Aggregation in Federated Learning


Sep 29, 2021
Chien-Sheng Yang, Jinhyun So, Chaoyang He, Songze Li, Qian Yu, Salman Avestimehr


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Private Retrieval, Computing and Learning: Recent Progress and Future Challenges


Jul 30, 2021
Sennur Ulukus, Salman Avestimehr, Michael Gastpar, Syed Jafar, Ravi Tandon, Chao Tian


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Verifiable Coded Computing: Towards Fast, Secure and Private Distributed Machine Learning


Jul 27, 2021
Tingting Tang, Ramy E. Ali, Hanieh Hashemi, Tynan Gangwani, Salman Avestimehr, Murali Annavaram


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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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Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning


Jun 07, 2021
Jinhyun So, Ramy E. Ali, Basak Guler, Jiantao Jiao, 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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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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Coded Computing for Low-Latency Federated Learning over Wireless Edge Networks


Nov 12, 2020
Saurav Prakash, Sagar Dhakal, Mustafa Akdeniz, Yair Yona, Shilpa Talwar, Salman Avestimehr, Nageen Himayat

* Final version to appear in the first issue of the IEEE JSAC Series on Machine Learning for Communications and Networks 

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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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Train Where the Data is: A Case for Bandwidth Efficient Coded Training


Oct 22, 2019
Zhifeng Lin, Krishna Giri Narra, Mingchao Yu, Salman Avestimehr, Murali Annavaram

* 10 pages, Under submission 

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Collage Inference: Achieving low tail latency during distributed image classification using coded redundancy models


Jun 05, 2019
Krishna Narra, Zhifeng Lin, Ganesh Ananthanarayanan, Salman Avestimehr, Murali Annavaram

* 4 pages, CodML workshop at International Conference on Machine Learning (ICML 2019). arXiv admin note: text overlap with arXiv:1904.12222 

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Collage Inference: Tolerating Stragglers in Distributed Neural Network Inference using Coding


Apr 27, 2019
Krishna Giri Narra, Zhifeng Lin, Ganesh Ananthanarayanan, Salman Avestimehr, Murali Annavaram

* 13 pages, 13 figures, Under submission 

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Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training


Nov 08, 2018
Youjie Li, Mingchao Yu, Songze Li, Salman Avestimehr, Nam Sung Kim, Alexander Schwing


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GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training


Nov 08, 2018
Mingchao Yu, Zhifeng Lin, Krishna Narra, Songze Li, Youjie Li, Nam Sung Kim, Alexander Schwing, Murali Annavaram, Salman Avestimehr


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Distributed Solution of Large-Scale Linear Systems via Accelerated Projection-Based Consensus


Dec 11, 2017
Navid Azizan-Ruhi, Farshad Lahouti, Salman Avestimehr, Babak Hassibi


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A Sampling Theory Perspective of Graph-based Semi-supervised Learning


May 26, 2017
Aamir Anis, Aly El Gamal, Salman Avestimehr, Antonio Ortega


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Active Learning for Community Detection in Stochastic Block Models


May 08, 2016
Akshay Gadde, Eyal En Gad, Salman Avestimehr, Antonio Ortega

* 5 pages, 3 figures, To appear in IEEE International Symposium on Information Theory 2016 

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