Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges

14 November 2021

Mohammad M. Al-Quraan

Mérouane Debbah

Papers citing "Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges"

38 / 88 papers shown

Title
Hierarchical Federated Learning Across Heterogeneous Cellular Networks Mehdi Salehi Heydar Abad Emre Ozfatura Deniz Gunduz Ozgur Ercetin FedML 116 309 0 05 Sep 2019
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 83 4,470 0 21 Aug 2019
Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges Solmaz Niknam Harpreet S. Dhillon J. H. Reed 55 600 0 30 Jul 2019
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection Yue Liu Zeyi Wen Zhaomin Wu Sixu Hu Naibo Wang Yuan N. Li Xu Liu Bingsheng He FedML 74 987 0 23 Jul 2019
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare Yiqiang Chen Jindong Wang Chaohui Yu Wen Gao Xin Qin FedML 60 710 0 22 Jul 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 123 2,311 0 04 Jul 2019
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations Debraj Basu Deepesh Data C. Karakuş Suhas Diggavi MQ 38 403 0 06 Jun 2019
Accelerating DNN Training in Wireless Federated Edge Learning Systems Jinke Ren Guanding Yu Guangyao Ding FedML 40 169 0 23 May 2019
BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning Abhijit Guha Roy Shayan Siddiqui Sebastian Polsterl Nassir Navab Christian Wachinger FedML OOD MedIm 45 306 0 16 May 2019
Client-Edge-Cloud Hierarchical Federated Learning Lumin Liu Jun Zhang S. H. Song Khaled B. Letaief FedML 56 736 0 16 May 2019
Random Search and Reproducibility for Neural Architecture Search Liam Li Ameet Talwalkar OOD 51 719 0 20 Feb 2019
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 88 2,652 0 04 Feb 2019
Federated Deep Reinforcement Learning H. Zhuo Wenfeng Feng Yufeng Lin Qian Xu Qiang Yang FedML OffRL 27 89 0 24 Jan 2019
Federated Learning via Over-the-Air Computation Kai Yang Tao Jiang Yuanming Shi Z. Ding FedML 57 874 0 31 Dec 2018
Broadband Analog Aggregation for Low-Latency Federated Edge Learning (Extended Version) Guangxu Zhu Yong Wang Kaibin Huang FedML 45 638 0 30 Dec 2018
Federated Optimization in Heterogeneous Networks Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 83 5,105 0 14 Dec 2018
Wireless Network Intelligence at the Edge Jihong Park S. Samarakoon M. Bennis Mérouane Debbah 87 519 0 07 Dec 2018
Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data Eunjeong Jeong Seungeun Oh Hyesung Kim Jihong Park M. Bennis Seong-Lyun Kim FedML 52 596 0 28 Nov 2018
Federated Learning with Non-IID Data Yue Zhao Meng Li Liangzhen Lai Naveen Suda Damon Civin Vikas Chandra FedML 134 2,547 0 02 Jun 2018
Federated Learning for Ultra-Reliable Low-Latency V2V Communications S. Samarakoon M. Bennis Walid Saad Merouane Debbah 44 228 0 11 May 2018
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge Takayuki Nishio Ryo Yonetani FedML 104 1,390 0 23 Apr 2018
All Reality: Virtual, Augmented, Mixed (X), Mediated (X,Y), and Multimediated Reality Steve Mann Tom A. Furness Yu Yuan Jay Iorio Zixin Wang 45 139 0 20 Apr 2018
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang Tiffany Tuor Theodoros Salonidis K. Leung C. Makaya T. He Kevin S. Chan 200 1,692 0 14 Apr 2018
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Chengyue Wu Song Han Huizi Mao Yu Wang W. Dally 102 1,394 0 05 Dec 2017
Deep Reinforcement Learning that Matters Peter Henderson Riashat Islam Philip Bachman Joelle Pineau Doina Precup David Meger OffRL 101 1,940 0 19 Sep 2017
Channel Pruning for Accelerating Very Deep Neural Networks Yihui He Xiangyu Zhang Jian Sun 189 2,513 0 19 Jul 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 430 129,831 0 12 Jun 2017
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 83 1,791 0 30 May 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 267 4,620 0 18 Oct 2016
An overview of gradient descent optimization algorithms Sebastian Ruder ODL 177 6,170 0 15 Sep 2016
Data Programming: Creating Large Training Sets, Quickly Alexander Ratner Christopher De Sa Sen Wu Daniel Selsam Christopher Ré 118 713 0 25 May 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 229 17,235 0 17 Feb 2016
Quantized Convolutional Neural Networks for Mobile Devices Jiaxiang Wu Cong Leng Yuhang Wang Qinghao Hu Jian Cheng MQ 58 1,162 0 21 Dec 2015
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation N. Mayer Eddy Ilg Philip Häusser Philipp Fischer Daniel Cremers Alexey Dosovitskiy Thomas Brox 3DPC 47 2,625 0 07 Dec 2015
Cyclical Learning Rates for Training Neural Networks L. Smith ODL 111 2,515 0 03 Jun 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 225 19,448 0 09 Mar 2015
Hyperparameter Search in Machine Learning Marc Claesen B. De Moor 50 438 0 07 Feb 2015
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 275 7,883 0 13 Jun 2012