Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge

23 April 2018

Papers citing "Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge"

50 / 411 papers shown

Title
Fast Federated Edge Learning with Overlapped Communication and Computation and Channel-Aware Fair Client Scheduling M. E. Ozfatura Junlin Zhao Deniz Gündüz 32 15 0 14 Sep 2021
Cost-Effective Federated Learning in Mobile Edge Networks Bing Luo Xiang Li Shiqiang Wang Jianwei Huang Leandros Tassiulas FedML 57 72 0 12 Sep 2021
FedZKT: Zero-Shot Knowledge Transfer towards Resource-Constrained Federated Learning with Heterogeneous On-Device Models Lan Zhang Dapeng Wu Xiaoyong Yuan FedML 38 47 0 08 Sep 2021
Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection Shulai Zhang Zirui Li Quan Chen Wenli Zheng Jingwen Leng M. Guo FedML 59 32 0 08 Sep 2021
Statistical Estimation and Inference via Local SGD in Federated Learning Xiang Li Jiadong Liang Xiangyu Chang Zhihua Zhang FedML 27 4 0 03 Sep 2021
Asynchronous Federated Learning for Sensor Data with Concept Drift Yujing Chen Zheng Chai Yue Cheng Huzefa Rangwala FedML 24 32 0 01 Sep 2021
Federated Reinforcement Learning: Techniques, Applications, and Open Challenges Jiaju Qi Qihao Zhou Lei Lei Kan Zheng FedML 31 145 0 26 Aug 2021
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning S. Vargaftik Ran Ben-Basat Amit Portnoy Gal Mendelson Y. Ben-Itzhak Michael Mitzenmacher FedML 46 46 0 19 Aug 2021
Efficient Federated Meta-Learning over Multi-Access Wireless Networks Sheng Yue Ju Ren Jiang Xin Deyu Zhang Yaoxue Zhang W. Zhuang 28 38 0 14 Aug 2021
Evaluating Federated Learning for Intrusion Detection in Internet of Things: Review and Challenges Enrique Mármol Campos Pablo Fernández Saura Aurora González-Vidal José Luis Hernández Ramos Jorge Bernal Bernabé G. Baldini A. Gómez-Skarmeta 50 149 0 02 Aug 2021
Decentralized Deep Learning for Multi-Access Edge Computing: A Survey on Communication Efficiency and Trustworthiness Yuwei Sun H. Ochiai Hiroshi Esaki FedML 74 45 0 30 Jul 2021
A General Theory for Client Sampling in Federated Learning Yann Fraboni Richard Vidal Laetitia Kameni Marco Lorenzi FedML 12 13 0 26 Jul 2021
Federated Learning with Fair Worker Selection: A Multi-Round Submodular Maximization Approach Fengjiao Li Jia Liu Bo Ji FedML 22 4 0 25 Jul 2021
Communication Efficiency in Federated Learning: Achievements and Challenges Osama Shahid Seyedamin Pouriyeh R. Parizi Quan Z. Sheng Gautam Srivastava Liang Zhao FedML 40 74 0 23 Jul 2021
Fed-ensemble: Improving Generalization through Model Ensembling in Federated Learning Naichen Shi Fan Lai Raed Al Kontar Mosharaf Chowdhury FedML 31 35 0 21 Jul 2021
Communication-Efficient Hierarchical Federated Learning for IoT Heterogeneous Systems with Imbalanced Data A. Abdellatif N. Mhaisen Amr M. Mohamed A. Erbad Mohsen Guizani Z. Dawy W. Nasreddine FedML 58 93 0 14 Jul 2021
Management of Resource at the Network Edge for Federated Learning Silvana Trindade L. Bittencourt N. Fonseca 22 6 0 07 Jul 2021
Faithful Edge Federated Learning: Scalability and Privacy Meng Zhang Ermin Wei R. Berry FedML 26 44 0 30 Jun 2021
A Comprehensive Survey of Incentive Mechanism for Federated Learning Rongfei Zeng Chaobing Zeng Xingwei Wang Bo-wen Li Xiaowen Chu FedML 31 95 0 27 Jun 2021
Is Shapley Value fair? Improving Client Selection for Mavericks in Federated Learning Jiyue Huang Chi Hong L. Chen Stefanie Roos FedML 22 9 0 20 Jun 2021
Fine-Grained Data Selection for Improved Energy Efficiency of Federated Edge Learning A. Albaseer M. Abdallah Ala I. Al-Fuqaha A. Erbad 31 35 0 20 Jun 2021
On Large-Cohort Training for Federated Learning Zachary B. Charles Zachary Garrett Zhouyuan Huo Sergei Shmulyian Virginia Smith FedML 21 113 0 15 Jun 2021
Heterogeneous Federated Learning using Dynamic Model Pruning and Adaptive Gradient Sixing Yu P. Nguyen Ali Anwar Ali Jannesari 37 12 0 13 Jun 2021
Joint Client Scheduling and Resource Allocation under Channel Uncertainty in Federated Learning Madhusanka Manimel Wadu S. Samarakoon M. Bennis 18 51 0 12 Jun 2021
FedCCEA : A Practical Approach of Client Contribution Evaluation for Federated Learning S. K. Shyn Donghee Kim Kwangsu Kim FedML 14 22 0 04 Jun 2021
Federated Neural Collaborative Filtering V. Perifanis P. Efraimidis FedML 15 92 0 02 Jun 2021
Node Selection Toward Faster Convergence for Federated Learning on Non-IID Data Hongda Wu Ping Wang FedML 29 135 0 14 May 2021
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning Yann Fraboni Richard Vidal Laetitia Kameni Marco Lorenzi FedML 15 184 0 12 May 2021
Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates Laizhong Cui Xiaoxin Su Yipeng Zhou Yi Pan FedML 38 36 0 10 May 2021
Loss Tolerant Federated Learning Pengyuan Zhou Pei Fang Pan Hui 13 16 0 08 May 2021
A Hybrid Architecture for Federated and Centralized Learning Ahmet M. Elbir Sinem Coleri Anastasios K. Papazafeiropoulos P. Kourtessis Symeon Chatzinotas FedML 18 35 0 07 May 2021
FedGL: Federated Graph Learning Framework with Global Self-Supervision Chuan Chen Weibo Hu Ziyue Xu Zibin Zheng FedML 27 54 0 07 May 2021
Pervasive AI for IoT applications: A Survey on Resource-efficient Distributed Artificial Intelligence Emna Baccour N. Mhaisen A. Abdellatif A. Erbad Amr M. Mohamed Mounir Hamdi Mohsen Guizani 30 86 0 04 May 2021
PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments Fan Mo Hamed Haddadi Kleomenis Katevas Eduard Marin Diego Perino N. Kourtellis FedML 39 244 0 29 Apr 2021
Secure and Efficient Federated Learning Through Layering and Sharding Blockchain Shuo Yuan Bin Cao Yaohua Sun Zhiguo Wan M. Peng 22 20 0 27 Apr 2021
Semi-Decentralized Federated Edge Learning for Fast Convergence on Non-IID Data Yuchang Sun Jiawei Shao Yuyi Mao Jessie Hui Wang Jun Zhang FedML 41 39 0 26 Apr 2021
FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems Li Li Moming Duan Duo Liu Yu Zhang Ao Ren Xianzhang Chen Yujuan Tan Chengliang Wang FedML 31 43 0 15 Apr 2021
Communication Efficient Federated Learning with Adaptive Quantization Yuzhu Mao Zihao Zhao Guangfeng Yan Yang Liu Tian-Shing Lan Linqi Song Wenbo Ding MQ 22 10 0 13 Apr 2021
Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges Dinh C. Nguyen Ming Ding Viet Quoc Pham P. Pathirana Long Bao Jun Seneviratne Jun Li Dusit Niyato Life Fellow Ieee Poor FedML 36 418 0 05 Apr 2021
Threshold-Based Data Exclusion Approach for Energy-Efficient Federated Edge Learning A. Albaseer M. Abdallah Ala I. Al-Fuqaha A. Erbad 35 12 0 30 Mar 2021
Privacy and Trust Redefined in Federated Machine Learning Pavlos Papadopoulos Will Abramson A. Hall Nikolaos Pitropakis William J. Buchanan 33 42 0 29 Mar 2021
Optimization of User Selection and Bandwidth Allocation for Federated Learning in VLC/RF Systems Chuanhong Liu Caili Guo Yang Yang Mingzhe Chen H. Vincent Poor Shuguang Cui 9 10 0 05 Mar 2021
Temporal-Structure-Assisted Gradient Aggregation for Over-the-Air Federated Edge Learning Dian Fan Xiaojun Yuan Y. Zhang FedML 13 24 0 03 Mar 2021
Blockchain-Based Federated Learning in Mobile Edge Networks with Application in Internet of Vehicles Rui-cang Wang Heju Li Erwu Liu 18 11 0 01 Mar 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 189 268 0 26 Feb 2021
Cybersecurity Threats in Connected and Automated Vehicles based Federated Learning Systems Ranwa Al Mallah Godwin Badu-Marfo Bilal Farooq 37 19 0 26 Feb 2021
Data-Aware Device Scheduling for Federated Edge Learning Afaf Taik Zoubeir Mlika Soumaya Cherkaoui 17 38 0 18 Feb 2021
A Federated Data-Driven Evolutionary Algorithm Jinjin Xu Yaochu Jin W. Du Sai Gu FedML 68 35 0 16 Feb 2021
On the Impact of Device and Behavioral Heterogeneity in Federated Learning A. Abdelmoniem Chen-Yu Ho Pantelis Papageorgiou Muhammad Bilal Marco Canini FedML 11 18 0 15 Feb 2021
FedProf: Selective Federated Learning with Representation Profiling Wentai Wu Ligang He Weiwei Lin Carsten Maple FedML 36 1 0 02 Feb 2021