Exploring Machine Learning Models for Federated Learning: A Review of Approaches, Performance, and Limitations

17 November 2023

Papers citing "Exploring Machine Learning Models for Federated Learning: A Review of Approaches, Performance, and Limitations"

20 / 20 papers shown

Title
A compressive multi-kernel method for privacy-preserving machine learning Thee Chanyaswad Jerome Chang S. Kung 47 26 0 20 Jun 2021
Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges Dinh C. Nguyen Ming Ding Quoc-Viet Pham P. Pathirana Long Bao Jun Seneviratne Jun Li Dusit Niyato Life Fellow Ieee Poor FedML 91 431 0 05 Apr 2021
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 327 873 0 01 Mar 2021
From Federated Learning to Federated Neural Architecture Search: A Survey Hangyu Zhu Haoyu Zhang Yaochu Jin FedML OOD AI4CE 77 151 0 12 Sep 2020
Particle Swarm Optimized Federated Learning For Industrial IoT and Smart City Services Basheer Qolomany Kashif Ahmad Ala I. Al-Fuqaha Junaid Qadir 58 65 0 05 Sep 2020
Collaborative Fairness in Federated Learning Lingjuan Lyu Xinyi Xu Qian Wang FedML 68 193 0 27 Aug 2020
Privacy-preserving Voice Analysis via Disentangled Representations Ranya Aloufi Hamed Haddadi David E. Boyle DRL 82 58 0 29 Jul 2020
Less is More: A privacy-respecting Android malware classifier using Federated Learning Rafa Gálvez Veelasha Moonsamy Claudia Díaz FedML 29 30 0 16 Jul 2020
Blockchain-Federated-Learning and Deep Learning Models for COVID-19 detection using CT Imaging R. Kumar A. Khan Sinmin Zhang Jay Kumar Wenyong Wang Yousif Abuidris Zakria Waqas Amin Sidra Shafiq WenYong Wang OOD FedML 72 328 0 10 Jul 2020
Federated Learning and Differential Privacy: Software tools analysis, the Sherpa.ai FL framework and methodological guidelines for preserving data privacy Nuria Rodríguez Barroso G. Stipcich Daniel Jiménez-López José Antonio Ruiz-Millán Eugenio Martínez-Cámara Gerardo González-Seco M. V. Luzón M. Veganzones Francisco Herrera 55 102 0 02 Jul 2020
PIRATE: A Blockchain-based Secure Framework of Distributed Machine Learning in 5G Networks Sicong Zhou Huawei Huang Wuhui Chen Zibin Zheng Song Guo FedML 52 75 0 17 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 259 6,276 0 10 Dec 2019
Federated Learning for Edge Networks: Resource Optimization and Incentive Mechanism L. U. Khan Shashi Raj Pandey Nguyen H. Tran Walid Saad Zhu Han Minh N. H. Nguyen Choong Seon Hong FedML 57 385 0 06 Nov 2019
Federated Learning with Differential Privacy: Algorithms and Performance Analysis Kang Wei Jun Li Ming Ding Chuan Ma Heng Yang Farokhi Farhad Shi Jin Tony Q.S. Quek H. Vincent Poor FedML 125 1,616 0 01 Nov 2019
Reliable Federated Learning for Mobile Networks Jiawen Kang Zehui Xiong Dusit Niyato Y. Zou Yang Zhang Mohsen Guizani FedML 50 463 0 14 Oct 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 109 1,001 0 23 Jul 2019
Privacy-Preserving Classification with Secret Vector Machines Valentin Hartmann Konark Modi J. M. Pujol Robert West 56 14 0 08 Jul 2019
Robust and Communication-Efficient Federated Learning from Non-IID Data Felix Sattler Simon Wiedemann K. Müller Wojciech Samek FedML 74 1,361 0 07 Mar 2019
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,155 0 01 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,559 0 17 Feb 2016