Fetching the paper…
Reading the bibliography…
Federated learning (FL) is an emerging promising privacy-preserving machine learning paradigm and has raised more and more attention from researchers and developers.
Secure Multi-party Computation
Oded Goldreich. 1998 · 1998
Earlier work this paper cites.
A Survey of Homomorphic Encryption for Nonspecialists
Caroline Fontaine and Fabien Galand. 2007 · 2007
Earlier work this paper cites.
Bitcoin: A peer-to-peer electronic cash system
Satoshi Nakamoto. 2008 · 2008
Earlier work this paper cites.
Crypto-Nets: Neural Networks over Encrypted Data
Pengtao Xie, Misha Bilenko, Tom Finley, Ran Gilad-Bachrach, Kristin E. Lauter, and Michael Naehrig. 2014 · 2014
Earlier work this paper cites.
Privacy-Preserving Deep Learning. In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, Denver, CO, USA, October 12-16, 2015 . 1310–1321
Reza Shokri and Vitaly Shmatikov. 2015 · 2015
Earlier work this paper cites.
I Know What You Did on Your Smartphone: Inferring App Usage over Encrypted Data Traffic. In Proceedings of the 2015 IEEE Conference on Communications and Network Security, CNS ’15 . 433–441
Qinglong Wang, Amir Yahyavi, Bettina Kemme, and Wenbo He. 2015 · 2015
Earlier work this paper cites.
Analyzing Android Encrypted Network Traffic to Identify User Actions
Mauro Conti, Luigi Vincenzo Mancini, Riccardo Spolaor, and Nino Vincenzo Verde. 2016 · 2016
Earlier work this paper cites.
Federated Optimization: Distributed Machine Learning for On-Device Intelligence
Jakub Konečný, H. Brendan McMahan, Daniel Ramage, and Peter Richtárik. 2016 · 2016
Earlier work this paper cites.
Robust Optimization for Non-Convex Objectives. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA . 4705–4714
Robert S. Chen, Brendan Lucier, Yaron Singer, and Vasilis Syrgkanis. 2017 · 2017
Earlier work this paper cites.
Densely Connected Convolutional Networks. In 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, July 21-26, 2017 . 2261–2269
Gao Huang, Zhuang Liu, Laurens van der Maaten, and Kilian Q. Weinberger. 2017 · 2017
Earlier work this paper cites.
Communication-Efficient Learning of Deep Networks from Decentralized Data. In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 20-22 April 2017, Fort Lauderdale, FL, USA
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Agüera y Arcas. 2017 · 2017
Earlier work this paper cites.
Privacy-Preserving Deep Learning: Revisited and Enhanced. In Proceedings of Applications and Techniques in Information Security - 8th International Conference, ATIS ’17 (Communications in Computer and Information Science, Vol. 719) . 100–110
Le Trieu Phong, Yoshinori Aono, Takuya Hayashi, Lihua Wang, and Shiho Moriai. 2017 · 2017
Earlier work this paper cites.
ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases. In 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, July 21-26, 2017 . 3462–3471
Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, and Ronald M. Summers. 2017 · 2017
Earlier work this paper cites.
An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends. In 2017 IEEE International Congress on Big Data, BigData Congress 2017, Honolulu, HI, USA, June 25-30, 2017 . 557–564
Zibin Zheng, Shaoan Xie, Hongning Dai, Xiangping Chen, and Huaimin Wang. 2017 · 2017
Earlier work this paper cites.
Dropping Activation Outputs With Localized First-Layer Deep Network for Enhancing User Privacy and Data Security
Hao Dong, Chao Wu, Zhen Wei, and Yike Guo. 2018 · 2018
Earlier work this paper cites.
Federated Learning for Mobile Keyboard Prediction
Andrew Hard, Kanishka Rao, Rajiv Mathews, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, and Daniel Ramage. 2018 · 2018
Earlier work this paper cites.
Fully decentralized federated learning. In Third workshop on Bayesian Deep Learning (NeurIPS)
Anusha Lalitha, Shubhanshu Shekhar, Tara Javidi, and Farinaz Koushanfar. 2018 · 2018
Earlier work this paper cites.
Privacy-Preserving Personal Model Training. In Proceedings of the 2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation, IoTDI ’18 . 153–164
Sandra Servia Rodríguez, Liang Wang, Jianxin R. Zhao, Richard Mortier, and Hamed Haddadi. 2018 · 2018
Earlier work this paper cites.
DeepType: On-Device Deep Learning for Input Personalization Service with Minimal Privacy Concern
Mengwei Xu, Feng Qian, Qiaozhu Mei, Kang Huang, and Xuanzhe Liu. 2018 · 2018
Cited alongside, same era.
Applied Federated Learning: Improving Google Keyboard Query Suggestions
Timothy Yang, Galen Andrew, Hubert Eichner, Haicheng Sun, Wei Li, Nicholas Kong, Daniel Ramage, and Françoise Beaufays. 2018 · 2018
Cited alongside, same era.
Towards Federated Learning at Scale: System Design. In Proceedings of Machine Learning and Systems 2019, MLSys 2019, Stanford, CA, USA, March 31 - April 2, 2019
Kallista A. Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloé Kiddon, Jakub Konečný, Stefano Mazzocchi, Brendan McMahan, Timon Van Overveldt, David Petrou, Daniel Ramage, and Jason Roselander. 2019 · 2019
Cited alongside, same era.
Mixup Based Privacy Preserving Mixed Collaboration Learning. In Proceedings of the 13th IEEE International Conference on Service-Oriented System Engineering, SOSE ’19
Yingwei Fu, Huaimin Wang, Kele Xu, Haibo Mi, and Yijie Wang. 2019 · 2019
Cited alongside, same era.
Demystifying Illegal Mobile Gambling Apps. In WWW ’21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021 . ACM / IW3C2, 1447–1458
Yuhao Gao, Haoyu Wang, Li Li, Xiapu Luo, Guoai Xu, and Xuanzhe Liu. 2021 · 2021
Later among the works it cites.
DeepRec: On-device Deep Learning for Privacy-Preserving Sequential Recommendation in Mobile Commerce. In WWW ’21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021 . ACM / IW3C2, 900–911
Jialiang Han, Yun Ma, Qiaozhu Mei, and Xuanzhe Liu. 2021 · 2021
Later among the works it cites.
Meta-HAR: Federated Representation Learning for Human Activity Recognition. In WWW ’21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021 . 912–922
Chenglin Li, Di Niu, Bei Jiang, Xiao Zuo, and Jianming Yang. 2021b · 2021
Later among the works it cites.
Jun Li, Yumeng Shao, Kang Wei, Ming Ding, Chuan Ma, Long Shi, Zhu Han, and H. Vincent Poor. 2021c · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Peer-to-peer Federated Learning on Graphs
Anusha Lalitha, Osman Cihan Kilinc, Tara Javidi, and Farinaz Koushanfar. 2019 · 2019
Cited alongside, same era.
Moving Deep Learning into Web Browser: How Far Can We Go?. In The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019 . ACM, 1234–1244
Yun Ma, Dongwei Xiang, Shuyu Zheng, Deyu Tian, and Xuanzhe Liu. 2019 · 2019
Cited alongside, same era.
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning. In Proceedings of the 2019 IEEE Symposium on Security and Privacy, SP ’19 . 739–753
Milad Nasr, Reza Shokri, and Amir Houmansadr. 2019 · 2019
Cited alongside, same era.
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. In Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA
Mingxing Tan and Quoc V. Le. 2019 · 2019
Cited alongside, same era.
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning. In Proceedings of the 2019 IEEE Conference on Computer Communications, INFOCOM ’19 . 2512–2520
Zhibo Wang, Mengkai Song, Zhifei Zhang, Yang Song, Qian Wang, and Hairong Qi. 2019 · 2019
Cited alongside, same era.
A First Look at Deep Learning Apps on Smartphones. In The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019 . ACM, 2125–2136
Mengwei Xu, Jiawei Liu, Yuanqiang Liu, Felix Xiaozhu Lin, Yunxin Liu, and Xuanzhe Liu. 2019 · 2019
Cited alongside, same era.
Federated Machine Learning: Concept and Applications
Qiang Yang, Yang Liu, Tianjian Chen, and Yongxin Tong. 2019 · 2019
Cited alongside, same era.
On the Convergence of FedAvg on Non-IID Data. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020
Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, and Zhihua Zhang. 2020 · 2020
Cited alongside, same era.
Later among the works it cites.
A Blockchain-Based Decentralized Federated Learning Framework with Committee Consensus
Yuzheng Li, Chuan Chen, Nan Liu, Huawei Huang, Zibin Zheng, and Qiang Yan. 2021a · 2021
Later among the works it cites.
A Longitudinal Study of Removed Apps in iOS App Store. In WWW ’21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021 . ACM / IW3C2, 1435–1446
Fuqi Lin, Haoyu Wang, Liu Wang, and Xuanzhe Liu. 2021 · 2021
Later among the works it cites.
PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization. In WWW ’21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021 . 923–934
Bingyan Liu, Yao Guo, and Xiangqun Chen. 2021 · 2021
Later among the works it cites.
Communication Efficient Federated Generalized Tensor Factorization for Collaborative Health Data Analytics. In WWW ’21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021 . 171–182
Jing Ma, Qiuchen Zhang, Jian Lou, Li Xiong, and Joyce C. Ho. 2021 · 2021
Later among the works it cites.
Privacy considerations for sharing genomics data
Marie Oestreich, Dingfan Chen, Joachim L Schultze, Mario Fritz, and Matthias Becker. 2021 · 2021
Later among the works it cites.
A Credibility-aware Swarm-Federated Deep Learning Framework in Internet of Vehicles
Zhe Wang, Xinhang Li, Tianhao Wu, Chen Xu, and Lin Zhang. 2021 · 2021
Later among the works it cites.
Swarm Learning for decentralized and confidential clinical machine learning
Stefanie Warnat-Herresthal, Hartmut Schultze, Krishnaprasad Lingadahalli Shastry, Sathyanarayanan Manamohan, Saikat Mukherjee, Vishesh Garg, Ravi Sarveswara, Kristian Händler, Peter Pickkers, N Ahmad Aziz, et al · 2021
Later among the works it cites.
Risk Prediction of Cardiovascular Events by Exploration of Molecular Data with Explainable Artificial Intelligence
Annie M Westerlund, Johann S Hawe, Matthias Heinig, and Heribert Schunkert. 2021 · 2021
Later among the works it cites.
FEDERATED MORPHOMETRY FEATURE SELECTION FOR HIPPOCAMPAL MORPHOMETRY ASSOCIATED BETA-AMYLOID AND TAU PATHOLOGY
Jianfeng Wu, Qunxi Dong, Jie Zhang, Yi Su, Teresa Wu, Richard J Caselli, Eric M Reiman, Jieping Ye, Natasha Lepore, Kewei Chen, et al · 2021
Later among the works it cites.
Hierarchical Personalized Federated Learning for User Modeling. In WWW ’21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021 . 957–968
Jinze Wu, Qi Liu, Zhenya Huang, Yuting Ning, Hao Wang, Enhong Chen, Jinfeng Yi, and Bowen Zhou. 2021b · 2021
Later among the works it cites.
From cloud to edge: a first look at public edge platforms. In IMC ’21: ACM Internet Measurement Conference, Virtual Event, USA, November 2-4, 2021 . ACM, 37–53
Mengwei Xu, Zhe Fu, Xiao Ma, Li Zhang, Yanan Li, Feng Qian, Shangguang Wang, Ke Li, Jingyu Yang, and Xuanzhe Liu. 2021 · 2021
Later among the works it cites.
Characterizing Impacts of Heterogeneity in Federated Learning upon Large-Scale Smartphone Data. In WWW ’21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021 . 935–946
Chengxu Yang, Qipeng Wang, Mengwei Xu, Zhenpeng Chen, Kaigui Bian, Yunxin Liu, and Xuanzhe Liu. 2021 · 2021
Later among the works it cites.
Incentive Mechanism for Horizontal Federated Learning Based on Reputation and Reverse Auction. In WWW ’21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021 . 947–956
Jingwen Zhang, Yuezhou Wu, and Rong Pan. 2021 · 2021
Later among the works it cites.