Federated Learning for Ultra-Reliable Low-Latency V2V Communications

Federated Learning for Ultra-Reliable Low-Latency V2V Communications

11 May 2018

Merouane Debbah

Papers citing "Federated Learning for Ultra-Reliable Low-Latency V2V Communications"

16 / 66 papers shown

Title
Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networks S. Savazzi M. Nicoli V. Rampa FedML 18 306 0 27 Dec 2019
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 76 6,091 0 10 Dec 2019
L-FGADMM: Layer-Wise Federated Group ADMM for Communication Efficient Decentralized Deep Learning Anis Elgabli Jihong Park Sabbir Ahmed M. Bennis FedML 31 20 0 09 Nov 2019
Device Scheduling with Fast Convergence for Wireless Federated Learning Misha Sra C. Schmandt Z. Niu FedML 27 190 0 03 Nov 2019
Experienced Deep Reinforcement Learning with Generative Adversarial Networks (GANs) for Model-Free Ultra Reliable Low Latency Communication Ali Taleb Ieee Walid Saad Fellow Ieee Mohammad Mozaffari Member Ieee H. Vincent Poor Fellow 8 91 0 01 Nov 2019
Robust Federated Learning with Noisy Communication F. Ang Li Chen Senior Member Ieee Nan Zhao Senior Member Ieee Yunfei Chen Weidong Wang Feng Yu FedML 21 117 0 01 Nov 2019
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning Sai Praneeth Karimireddy Satyen Kale M. Mohri Sashank J. Reddi Sebastian U. Stich A. Suresh FedML 28 343 0 14 Oct 2019
Eavesdrop the Composition Proportion of Training Labels in Federated Learning Lixu Wang Shichao Xu Tianlin Li Qi Zhu FedML 20 62 0 14 Oct 2019
From Server-Based to Client-Based Machine Learning: A Comprehensive Survey Renjie Gu Chaoyue Niu Fan Wu Guihai Chen Chun Hu Chengfei Lyu Zhihua Wu 30 25 0 18 Sep 2019
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 72 4,421 0 21 Aug 2019
Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges Solmaz Niknam Harpreet S. Dhillon J. H. Reed 33 599 0 30 Jul 2019
Boosting Privately: Privacy-Preserving Federated Extreme Boosting for Mobile Crowdsensing Yang Liu Zhuo Ma Ximeng Liu Siqi Ma Surya Nepal R. Deng FedML 11 63 0 24 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 37 970 0 23 Jul 2019
Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications Moming Duan Duo Liu Xianzhang Chen Yujuan Tan Jinting Ren Lei Qiao Liang Liang FedML 16 193 0 02 Jul 2019
Unsupervised Deep Learning for Ultra-reliable and Low-latency Communications Chengjian Sun Chenyang Yang 12 15 0 26 Apr 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 24 2,634 0 04 Feb 2019