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As an emerging technique, Federated Learning (FL) can jointly train a global model with the data remaining locally, which effectively solves the problem of data privacy protection through the encryption mechanism.
Guidelines for performing systematic literature reviews in software engineering (version 2.3)
Kitchenham B.A · 2007
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Communication-efficient learning of deep networks from decentralized data
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Agüera y Arcas · 2017
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Hardy Stephen, Henecka Wilko, Ivey-Law Hamish, Nock Richard, Patrini Giorgio, Smith Guillaume, and Thorne Brian · 2017
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Differentially private federated learning: A client level perspective
Geyer Robin C, Klein Tassilo, and Nabi Moin · 2017
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Regulation (eu) 2016/679 of the european parliament and of the council on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing directive 95/46/ec (general data protection regulation)
EU · 2018
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Federated learning for mobile keyboard prediction
Hard Andrew, Rao Kanishka, Mathews Rajiv, Ramaswamy Swaroop, Beaufays Françoise, Augenstein Sean, Eichner Hubert, Kiddon Chloé, and Ramage Daniel · 2018
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Investigation of empirical researches in software engineering
Zhang L, Pu MY, Liu YJ, Tian JH, Yue T, and Jiang J · 2018
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Applied federated learning: Improving google keyboard query suggestions
Yang Timothy, Andrew Galen, Eichner Hubert, Sun Haicheng, Li Wei, Kong Nicholas, Ramage Daniel, and Beaufays Françoise · 2018
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Human activity recognition using federated learning
Konstantin Sozinov, Vladimir Vlassov, and Sarunas Girdzijauskas · 2018
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Federated Learning
Hartmann Florian · 2018
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Federated learning of predictive models from federated electronic health records
Theodora S. Brisimi, Ruidi Chen, Theofanie Mela, Alex Olshevsky, Ioannis Ch. Paschalidis, and Wei Shi · 2018
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Fadl: Federated-autonomous deep learning for distributed electronic health record
Liu Dianbo, Miller Timothy, Sayeed Raheel, and Mandl Kenneth D · 2018
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Loadaboost: Loss-based adaboost federated machine learning on medical data
Huang Li, Yin Yifeng, Fu Zeng, Zhang Shifa, Deng Hao, and Liu Dianbo · 2018
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Multi-institutional deep learning modeling without sharing patient data: A feasibility study on brain tumor segmentation
Micah J. Sheller, G. Anthony Reina, Brandon Edwards, Jason Martin, and Spyridon Bakas · 2018
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Federated region-learning: An edge computing based framework for urban environment sensing
Binxuan Hu, Yujia Gao, Liang Liu, and Huadong Ma · 2018
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Secure federated transfer learning
Liu Yang, Chen Tianjian, and Yang Qiang · 2018
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Federated meta-learning with fast convergence and efficient communication
Chen Fei, Luo Mi, Dong Zhenhua, Li Zhenguo, and He Xiuqiang · 2018
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Wisdom of the machines: federated learning using OPAL
Alotaibi Abdulrahman et al · 2018
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A performance evaluation of federated learning algorithms
Adrian Nilsson, Simon Smith, Gregor Ulm, Emil Gustavsson, and Mats Jirstrand · 2018
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On the convergence of federated optimization in heterogeneous networks
Anit Kumar Sahu, Tian Li, Maziar Sanjabi, Manzil Zaheer, Ameet Talwalkar, and Virginia Smith · 2018
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Advances and open problems in federated learning
Kairouz Peter, McMahan H Brendan, Avent Brendan, Bellet Aurélien, Bennis Mehdi, Bhagoji Arjun Nitin, Bonawitz Keith, Charles Zachary, Cormode Graham, Cummings Rachel, et al · 2019
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Federated learning for healthcare informatics
Jie Xu and Fei Wang · 2019
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Federated learning for wireless communications: Motivation, opportunities and challenges
Niknam Solmaz, Dhillon Harpreet S, and Reed Jeffrey H · 2019
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Secure distributed on-device learning networks with byzantine adversaries
Yanjie Dong, Julian Cheng, Md. Jahangir Hossain, and Victor C. M. Leung · 2019
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Federated learning
Yang Qiang, Liu Yang, Cheng Yong, Kang Yan, Chen Tianjian, and Yu Han · 2019
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Federated machine learning: Concept and applications
Qiang Yang, Yang Liu, Tianjian Chen, and Yongxin Tong · 2019
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Quantification of the leakage in federated learning
Li Zhaorui, Huang Zhicong, Chen Chaochao, and Hong Cheng · 2019
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Multi-task network anomaly detection using federated learning
Ying Zhao, Junjun Chen, Di Wu, Jian Teng, and Shui Yu · 2019
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Dïot: A federated self-learning anomaly detection system for iot
Thien Duc Nguyen, Samuel Marchal, Markus Miettinen, Hossein Fereidooni, N. Asokan, and Ahmad-Reza Sadeghi · 2019
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Federated wireless network intrusion detection
Burak Cetin, Alina Lazar, Jinoh Kim, Alex Sim, and Kesheng Wu · 2019
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Federated deep learning for immersive virtual reality over wireless networks
Mingzhe Chen, Omid Semiari, Walid Saad, Xuanlin Liu, and Changchuan Yin · 2019
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Real-world image datasets for federated learning
Luo Jiahuan, Wu Xueyang, Luo Yun, Huang Anbu, Huang Yunfeng, Liu Yang, and Yang Qiang · 2019
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Collaborative learning on the edges: A case study on connected vehicles
Sidi Lu, Yongtao Yao, and Weisong Shi · 2019
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Federated learning for keyword spotting
David Leroy, Alice Coucke, Thibaut Lavril, Thibault Gisselbrecht, and Joseph Dureau · 2019
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Federated learning of n-gram language models
Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, and Michael Riley · 2019
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Federated learning for emoji prediction in a mobile keyboard
Ramaswamy Swaroop, Mathews Rajiv, Rao Kanishka, and Beaufays Françoise · 2019
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Federated learning of out-of-vocabulary words
Chen Mingqing, Mathews Rajiv, Ouyang Tom, and Beaufays Françoise · 2019
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Hhhfl: Hierarchical heterogeneous horizontal federated learning for electroencephalography
Gao Dashan, Ju Ce, Wei Xiguang, Liu Yang, Chen Tianjian, and Yang Qiang · 2019
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Privacy preserving qoe modeling using collaborative learning
Selim Ickin, Konstantinos Vandikas, and Markus Fiedler · 2019
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A federated learning approach for mobile packet classification
Bakopoulou Evita, Tillman Balint, and Markopoulou Athina · 2019
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Federated uncertainty-aware learning for distributed hospital EHR data
Sabri Boughorbel, Fethi Jarray, Neethu Venugopal, Shabir Moosa, Haithum Elhadi, and Michel Makhlouf · 2019
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Privacy preserving pregnancy weight gain management: demo abstract
Chetanya Puri, Koustabh Dolui, Gerben Kooijman, Felipe Masculo, Shannon Van Sambeek, Sebastiaan Den Boer, Sam Michiels, Hans Hallez, Stijn Luca, and Bart Vanrumste · 2019
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Patient clustering improves efficiency of federated machine learning to predict mortality and hospital stay time using distributed electronic medical records
Li Huang, Andrew L. Shea, Huining Qian, Aditya Masurkar, Hao Deng, and Dianbo Liu · 2019
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Differential privacy-enabled federated learning for sensitive health data
Choudhury Olivia, Gkoulalas-Divanis Aris, Salonidis Theodoros, Sylla Issa, Park Yoonyoung, Hsu Grace, and Das Amar · 2019
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Federated and differentially private learning for electronic health records
Pfohl Stephen R, Dai Andrew M, and Heller Katherine · 2019
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Federated machine learning with anonymous random hybridization (fearh) on medical records
Cui Jianfei and Liu Dianbo · 2019
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Privacy-preserving federated brain tumour segmentation
Wenqi Li, Fausto Milletarì, Daguang Xu, Nicola Rieke, Jonny Hancox, Wentao Zhu, Maximilian Baust, Yan Cheng, Sébastien Ourselin, M. Jorge Cardoso, and Andrew Feng · 2019
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Braintorrent: A peer-to-peer environment for decentralized federated learning
Roy Abhijit Guha, Siddiqui Shayan, Pölsterl Sebastian, Navab Nassir, and Wachinger Christian · 2019
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Federated Machine Learning: A Distributed Approach to Pain Expression Recognition in Healthcare
TOBIS Nicolas · 2019
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Two-stage federated phenotyping and patient representation learning
Dianbo Liu, Dmitriy Dligach, and Timothy A. Miller · 2019
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Environmental monitoring based on fog computing paradigm and internet of things
Wendong Wang, Cheng Feng, Bo Zhang, and Hui Gao · 2019
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Energy demand prediction with federated learning for electric vehicle networks
Yuris Mulya Saputra, Dinh Thai Hoang, Diep N. Nguyen, Eryk Dutkiewicz, Markus Dominik Mueck, and Srikathyayani Srikanteswara · 2019
Cited alongside, same era.
Time-dependent and Privacy-Preserving Decentralized Routing using Federated Learning
Samal Chinmaya · 2019
Cited alongside, same era.
Power demand response incentive pricing model
Kun Zhang, Yuliang Shi, Yuecan Liu, and Zhongmin Yan · 2019
Cited alongside, same era.
FC-SLAM: federated learning enhanced distributed visual-lidar SLAM in cloud robotic system
Zhaoran Li, Lujia Wang, Lingxin Jiang, and Cheng-Zhong Xu · 2019
Cited alongside, same era.
Liu Boyi, Wang Lujia, Liu Ming, and Xu Cheng-Zhong · 2019
Cited alongside, same era.
Federated learning: Challenges, methods, and future directions
Tian Li, Anit Kumar Sahu, Ameet Talwalkar, and Virginia Smith · 2020
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Preserving data privacy via federated learning: Challenges and solutions
Zengpeng Li, Vishal Sharma, and Saraju P. Mohanty · 2020
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Federated learning in mobile edge networks: A comprehensive survey
Wei Yang Bryan Lim, Nguyen Cong Luong, Dinh Thai Hoang, Yutao Jiao, Ying-Chang Liang, Qiang Yang, Dusit Niyato, and Chunyan Miao · 2020
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The future of digital health with federated learning
Nicola Rieke, Jonny Hancox, Wenqi Li, Fausto Milletari, Holger Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu N. Galtier, Bennett A. Landman, Klaus H. Maier-Hein, Sébastien Ourselin, Micah J. Sheller, Ronald M. Summers, Andrew Trask, Daguang Xu, Maximilian Baust, and M. Jorge Cardoso · 2020
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Threats to federated learning: A survey
Lingjuan Lyu, Han Yu, and Qiang Yang · 2020
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Liang Xinle, Liu Yang, Chen Tianjian, Liu Ming, and Yang Qiang · 2019
Cited alongside, same era.
Lifelong federated reinforcement learning: A learning architecture for navigation in cloud robotic systems
Boyi Liu, Lujia Wang, and Ming Liu · 2019
Cited alongside, same era.
FFD: A federated learning based method for credit card fraud detection
Wensi Yang, Yuhang Zhang, Kejiang Ye, Li Li, and Cheng-Zhong Xu · 2019
Cited alongside, same era.
Towards federated graph learning for collaborative financial crimes detection
Suzumura Toyotaro, Zhou Yi, Barcardo Natahalie, Ye Guangnan, Houck Keith, Kawahara Ryo, Anwar Ali, Stavarache Lucia Larise, Klyashtorny Daniel, Ludwig Heiko, et al · 2019
Cited alongside, same era.
Federated learning of unsegmented chinese text recognition model
Xinghua Zhu, Jianzong Wang, Zhenhou Hong, Tian Xia, and Jing Xiao · 2019
Cited alongside, same era.
Federated learning assisted interactive EDA with dual probabilistic models for personalized search
Yang Chen, Xiaoyan Sun, and Yao Hu · 2019
Cited alongside, same era.
Federated topic modeling
Di Jiang, Yuanfeng Song, Yongxin Tong, Xueyang Wu, Weiwei Zhao, Qian Xu, and Qiang Yang · 2019
Cited alongside, same era.
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On safeguarding privacy and security in the framework of federated learning
Chuan Ma, Jun Li, Ming Ding, Howard H. Yang, Feng Shu, Tony Q. S. Quek, and H. Vincent Poor · 2020
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Inverting gradients–how easy is it to break privacy in federated learning?
Geiping Jonas, Bauermeister Hartmut, Dröge Hannah, and Moeller Michael · 2020
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Resources for: Conducting a systematic review
University of Minnesota · 2020
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Federated learning for task and resource allocation in wireless high altitude balloon networks
Wang Sihua, Chen Mingzhe, Yin Changchuan, Saad Walid, Hong Choong Seon, Cui Shuguang, and Poor H Vincent · 2020
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Federated learning based mobile edge computing for augmented reality applications
Chen Dawei, Xie Linda Jiang, Kim BaekGyu, Wang Li, Hong Choong Seon, Wang Li-Chun, and Han Zhu · 2020
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PMF: A privacy-preserving human mobility prediction framework via federated learning
Jie Feng, Can Rong, Funing Sun, Diansheng Guo, and Yong Li · 2020
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An on-device federated learning approach for cooperative anomaly detection
Ito Rei, Tsukada Mineto, and Matsutani Hiroki · 2020
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Federated learning for vision-and-language grounding problems
Fenglin Liu, Xian Wu, Shen Ge, Wei Fan, and Yuexian Zou · 2020
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A multicenter random forest model for effective prognosis prediction in collaborative clinical research network
Jin Li, Yu Tian, Yan Zhu, Tianshu Zhou, Jun Li, Kefeng Ding, and Jingsong Li · 2020
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Li Xiaoxiao, Gu Yufeng, Dvornek Nicha, Staib Lawrence, Ventola Pamela, and Duncan James S · 2020
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Facing small and biased data dilemma in drug discovery with federated learning
Xiong Zhaoping, Cheng Ziqiang, Liu Xiaohong, Wang Dingyan, Luo Xiaomin, Zheng Mingyue, and Jiang Hualiang · 2020
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Fl-qsar: a federated learning based qsar prototype for collaborative drug discovery
Chen Shaoqi, Xue Dongyu, Chuai Guohui, Yang Qiang, and Liu Qi · 2020
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Fedhealth: A federated transfer learning framework for wearable healthcare
Chen Yiqiang, Qin Xin, Wang Jindong, Yu Chaohui, and Gao Wen · 2020
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Fedner: Medical named entity recognition with federated learning
Ge Suyu, Wu Fangzhao, Wu Chuhan, Qi Tao, Huang Yongfeng, and Xie Xing · 2020
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Federated learning in vehicular edge computing: A selective model aggregation approach
Dongdong Ye, Rong Yu, Miao Pan, and Zhu Han · 2020
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Federated learning meets contract theory: Energy-efficient framework for electric vehicle networks
Mulya Saputra Yuris, Nguyen Diep N, Hoang Dinh Thai, Vu Thang Xuan, Dutkiewicz Eryk, and Chatzinotas Symeon · 2020
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Exploiting unlabeled data in smart cities using federated learning
Albaseer Abdullatif, Ciftler Bekir Sait, Abdallah Mohamed, and Al-Fuqaha Ala · 2020
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Privacy-preserving traffic flow prediction: A federated learning approach
Liu Yi, James JQ, Kang Jiawen, Niyato Dusit, and Zhang Shuyu · 2020
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Distributed federated learning for ultra-reliable low-latency vehicular communications
Sumudu Samarakoon, Mehdi Bennis, Walid Saad, and Mérouane Debbah · 2020
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Federated learning for localization: A privacy-preserving crowdsourcing method
Ciftler Bekir Sait, Albaseer Abdullatif, Lasla Noureddine, and Abdallah Mohamed · 2020
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Fedvision: An online visual object detection platform powered by federated learning
Yang Liu, Anbu Huang, Yun Luo, He Huang, Youzhi Liu, Yuanyuan Chen, Lican Feng, Tianjian Chen, Han Yu, and Qiang Yang · 2020
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Federated learning-based cognitive detection of jamming attack in flying ad-hoc network
Nishat I. Mowla, Nguyen H. Tran, Inshil Doh, and Kijoon Chae · 2020
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Aussel Nicolas, Chabridon Sophie, and Petetin Yohan · 2020
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Fedrec: Privacy-preserving news recommendation with federated learning
Qi Tao, Wu Fangzhao, Wu Chuhan, Huang Yongfeng, and Xie Xing · 2020
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Federated neuromorphic learning of spiking neural networks for low-power edge intelligence
Skatchkovsky Nicolas, Jang Hyeryung, and Simeone Osvaldo · 2020
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Focus: Dealing with label quality disparity in federated learning
Chen Yiqiang, Yang Xiaodong, Qin Xin, Yu Han, Chen Biao, and Shen Zhiqi · 2020
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Federated learning with matched averaging
Hongyi Wang, Mikhail Yurochkin, Yuekai Sun, Dimitris S. Papailiopoulos, and Yasaman Khazaeni · 2020
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Averaging is probably not the optimum way of aggregating parameters in federated learning
Peng Xiao, Samuel Cheng, Vladimir Stankovic, and Dejan Vukobratovic · 2020
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Data selection for federated learning with relevant and irrelevant data at clients
Tuor Tiffany, Wang Shiqiang, Ko Bong Jun, Liu Changchang, and Leung Kin K · 2020
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Federated continual learning with adaptive parameter communication
Yoon Jaehong, Jeong Wonyong, Lee Giwoong, Yang Eunho, and Hwang Sung Ju · 2020
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Fmore: An incentive scheme of multi-dimensional auction for federated learning in mec
Zeng Rongfei, Zhang Shixun, Wang Jiaqi, and Chu Xiaowen · 2020
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Toward an automated auction framework for wireless federated learning services market
Jiao Yutao, Wang Ping, Niyato Dusit, Lin Bin, and Kim Dong In · 2020
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Agarwal Alekh, Langford John, and Wei Chen-Yu · 2020
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Federated reinforcement learning for training control policies on multiple iot devices
Hyun-Kyo Lim, Ju-Bong Kim, Joo-Seong Heo, and Youn-Hee Han · 2020
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Performance analysis and optimization in privacy-preserving federated learning
Wei Kang, Li Jun, Ding Ming, Ma Chuan, Su Hang, Zhang Bo, and Poor H Vincent · 2020
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Differentially private asynchronous federated learning for mobile edge computing in urban informatics
Yunlong Lu, Xiaohong Huang, Yueyue Dai, Sabita Maharjan, and Yan Zhang · 2020
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Efficient and privacy-enhanced federated learning for industrial artificial intelligence
Meng Hao, Hongwei Li, Xizhao Luo, Guowen Xu, Haomiao Yang, and Sen Liu · 2020
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Privacy-preserving weighted federated learning within oracle-aided mpc framework
Zhu Huafei, Li Zengxiang, Cheah Merivyn, and Goh Rick Siow Mong · 2020
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A training-integrity privacy-preserving federated learning scheme with trusted execution environment
Yu Chen, Fang Luo, Tong Li, Tao Xiang, Zheli Liu, and Jin Li · 2020
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Privacyfl: A simulator for privacy-preserving and secure federated learning
Mugunthan Vaikkunth, Perairebueno Anton, and Kagal Lalana · 2020
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Anonymizing data for privacy-preserving federated learning
Choudhury Olivia, Gkoulalasdivanis Aris, Salonidis Theodoros, Sylla Issa, Park Yoonyoung, Hsu Grace, and Das Amar · 2020
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A practical privacy-preserving method in federateddeep learning
Feng Yan, Yang Xue, Fang Weijun, Xia Shu-Tao, and Tang Xiaohu · 2020
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A fairness-aware incentive scheme for federated learning
Han Yu, Zelei Liu, Yang Liu, Tianjian Chen, Mingshu Cong, Xi Weng, Dusit Niyato, and Qiang Yang · 2020
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Hierarchical incentive mechanism design for federated machine learning in mobile networks
Lim Wei Yang Bryan, Xiong Zehui, Miao Chunyan, Niyato Dusit, Yang Qiang, Leung Cyril, and Poor H Vincent · 2020
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A learning-based incentive mechanism for federated learning
Zhan Yufeng, Li Peng, Qu Zhihao, Zeng Deze, and Guo Song · 2020
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Fedcoin: A peer-to-peer payment system for federated learning
Liu Yuan, Sun Shuai, Ai Zhengpeng, Zhang Shuangfeng, Liu Zelei, and Yu Han · 2020
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