Federated Learning: Strategies for Improving Communication Efficiency

18 October 2016

Dave Bacon

Papers citing "Federated Learning: Strategies for Improving Communication Efficiency"

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Title
Distantly Supervised Relation Extraction in Federated Settings Dianbo Sui Yubo Chen Kang Liu Jun Zhao FedML 23 10 0 12 Aug 2020
FedSKETCH: Communication-Efficient and Private Federated Learning via Sketching Farzin Haddadpour Belhal Karimi Ping Li Xiaoyun Li FedML 58 31 0 11 Aug 2020
Holdout SGD: Byzantine Tolerant Federated Learning Shahar Azulay Lior Raz Amir Globerson Tomer Koren Y. Afek FedML 7 5 0 11 Aug 2020
FedNNNN: Norm-Normalized Neural Network Aggregation for Fast and Accurate Federated Learning Kenta Nagura S. Bian Takashi Sato FedML 20 0 0 11 Aug 2020
Scalable and Communication-efficient Decentralized Federated Edge Learning with Multi-blockchain Framework Jiawen Kang Zehui Xiong Chunxiao Jiang Yi Liu Song Guo Yang Zhang Dusit Niyato Cyril Leung Chunyan Miao FedML 38 40 0 10 Aug 2020
Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning Sai Praneeth Karimireddy Martin Jaggi Satyen Kale M. Mohri Sashank J. Reddi Sebastian U. Stich A. Suresh FedML 37 215 0 08 Aug 2020
LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets Ang Li Jingwei Sun Binghui Wang Lin Duan Sicheng Li Yiran Chen H. Li FedML 28 125 0 07 Aug 2020
SplitNN-driven Vertical Partitioning Iker Ceballos Vivek Sharma Eduardo Mugica Abhishek Singh Alberto Roman Praneeth Vepakomma Ramesh Raskar 31 73 0 07 Aug 2020
Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications Jihong Park S. Samarakoon Anis Elgabli Joongheon Kim M. Bennis Seong-Lyun Kim Mérouane Debbah 39 161 0 06 Aug 2020
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence Tianqing Zhu Dayong Ye Wei Wang Wanlei Zhou Philip S. Yu SyDa 38 125 0 05 Aug 2020
Can Adversarial Weight Perturbations Inject Neural Backdoors? Siddhant Garg Adarsh Kumar Vibhor Goel Yingyu Liang AAML 48 86 0 04 Aug 2020
The Need for Advanced Intelligence in NFV Management and Orchestration D. Manias Abdallah Shami 25 24 0 03 Aug 2020
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises S. Kevin Zhou H. Greenspan Christos Davatzikos James S. Duncan Bram van Ginneken A. Madabhushi Jerry L. Prince Daniel Rueckert Ronald M. Summers 58 627 0 02 Aug 2020
LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy Lichao Sun Jianwei Qian Xun Chen FedML 19 205 0 31 Jul 2020
Federated Visualization: A Privacy-preserving Strategy for Aggregated Visual Query Wei Chen Yating Wei Zhiyong Wang Shuyue Zhou Bingru Lin Zhiguang Zhou FedML 14 3 0 30 Jul 2020
Communication-Efficient Federated Learning via Optimal Client Sampling Mónica Ribero H. Vikalo FedML 29 93 0 30 Jul 2020
Dynamic Defense Against Byzantine Poisoning Attacks in Federated Learning Nuria Rodríguez-Barroso Eugenio Martínez-Cámara M. V. Luzón Francisco Herrera FedML AAML 24 35 0 29 Jul 2020
Accelerating Federated Learning over Reliability-Agnostic Clients in Mobile Edge Computing Systems Wentai Wu Ligang He Weiwei Lin Rui Mao 25 78 0 28 Jul 2020
VFL: A Verifiable Federated Learning with Privacy-Preserving for Big Data in Industrial IoT Anmin Fu Xianglong Zhang N. Xiong Yansong Gao Huaqun Wang FedML 24 174 0 27 Jul 2020
Federated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence Aaqib Saeed Flora D. Salim T. Ozcelebi J. Lukkien FedML SSL 101 99 0 25 Jul 2020
Federated Learning in the Sky: Aerial-Ground Air Quality Sensing Framework with UAV Swarms Yi Liu Jiangtian Nie Xuandi Li Syed Hassan Ahmed Wei Yang Bryan Lim Chunyan Miao 35 147 0 23 Jul 2020
A Systematic Literature Review on Federated Machine Learning: From A Software Engineering Perspective Sin Kit Lo Qinghua Lu Chen Wang Hye-Young Paik Liming Zhu FedML 53 83 0 22 Jul 2020
Byzantine-Resilient Secure Federated Learning Jinhyun So Başak Güler A. Avestimehr FedML 19 238 0 21 Jul 2020
Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review Yansong Gao Bao Gia Doan Zhi-Li Zhang Siqi Ma Jiliang Zhang Anmin Fu Surya Nepal Hyoungshick Kim AAML 36 221 0 21 Jul 2020
Fair and autonomous sharing of federate learning models in mobile Internet of Things Xiaohan Hao Wei Ren Ruoting Xiong Xianghan Zheng Tianqing Zhu N. Xiong FedML 8 1 0 21 Jul 2020
Incentives for Federated Learning: a Hypothesis Elicitation Approach Yang Liu Jiaheng Wei FedML 42 21 0 21 Jul 2020
Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach Yi Liu S. Garg Jiangtian Nie Yan Zhang Zehui Xiong Jiawen Kang M. S. Hossain FedML 39 378 0 19 Jul 2020
Tighter Generalization Bounds for Iterative Differentially Private Learning Algorithms Fengxiang He Bohan Wang Dacheng Tao FedML 28 17 0 18 Jul 2020
Learn distributed GAN with Temporary Discriminators Hui Qu Yikai Zhang Qi Chang Zhennan Yan Chao Chen Dimitris N. Metaxas FedML 21 16 0 17 Jul 2020
Asynchronous Federated Learning with Reduced Number of Rounds and with Differential Privacy from Less Aggregated Gaussian Noise Marten van Dijk Nhuong V. Nguyen Toan N. Nguyen Lam M. Nguyen Quoc Tran-Dinh Phuong Ha Nguyen FedML 23 28 0 17 Jul 2020
Prioritized Multi-Criteria Federated Learning Vito Walter Anelli Yashar Deldjoo Tommaso Di Noia Antonio Ferrara FedML 16 9 0 17 Jul 2020
Compression strategies and space-conscious representations for deep neural networks Giosuè Cataldo Marinò G. Ghidoli Marco Frasca D. Malchiodi 20 10 0 15 Jul 2020
FetchSGD: Communication-Efficient Federated Learning with Sketching D. Rothchild Ashwinee Panda Enayat Ullah Nikita Ivkin Ion Stoica Vladimir Braverman Joseph E. Gonzalez Raman Arora FedML 33 361 0 15 Jul 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 23 1,304 0 15 Jul 2020
FedBoosting: Federated Learning with Gradient Protected Boosting for Text Recognition Hanchi Ren Jingjing Deng Xianghua Xie Xiaoke Ma Yi-Cheng Wang FedML 19 11 0 14 Jul 2020
Quality Inference in Federated Learning with Secure Aggregation Balázs Pejó G. Biczók FedML 23 22 0 13 Jul 2020
VAFL: a Method of Vertical Asynchronous Federated Learning Tianyi Chen Xiao Jin Yuejiao Sun W. Yin FedML 23 160 0 12 Jul 2020
MeDaS: An open-source platform as service to help break the walls between medicine and informatics Liang Zhang Johann Li Ping Li Xiaoyuan Lu Peiyi Shen Guangming Zhu Syed Afaq Ali Shah Bennamoun Kun Qian Björn W. Schuller MedIm 26 6 0 12 Jul 2020
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning Hongyi Wang Kartik K. Sreenivasan Shashank Rajput Harit Vishwakarma Saurabh Agarwal Jy-yong Sohn Kangwook Lee Dimitris Papailiopoulos FedML 32 591 0 09 Jul 2020
Client Adaptation improves Federated Learning with Simulated Non-IID Clients Laura Rieger Rasmus M. Th. Høegh Lars Kai Hansen FedML 29 6 0 09 Jul 2020
Challenges of AI in Wireless Networks for IoT Ijaz Ahmad Shahriar Shahabuddin T. Kumar E. Harjula M. Meisel M. Juntti T. Sauter M. Ylianttila 15 18 0 09 Jul 2020
BlockFLow: An Accountable and Privacy-Preserving Solution for Federated Learning Vaikkunth Mugunthan Ravi Rahman Lalana Kagal FedML 21 40 0 08 Jul 2020
Coded Computing for Federated Learning at the Edge Saurav Prakash S. Dhakal M. Akdeniz A. Avestimehr N. Himayat FedML 26 11 0 07 Jul 2020
Sharing Models or Coresets: A Study based on Membership Inference Attack Hanlin Lu Changchang Liu T. He Shiqiang Wang Kevin S. Chan MIACV FedML 24 15 0 06 Jul 2020
Experiments of Federated Learning for COVID-19 Chest X-ray Images Boyi Liu Bingjie Yan Yize Zhou Yifan Yang Yixian Zhang OOD FedML 28 153 0 05 Jul 2020
Harnessing Wireless Channels for Scalable and Privacy-Preserving Federated Learning Anis Elgabli Jihong Park Chaouki Ben Issaid M. Bennis 28 54 0 03 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 28 100 0 02 Jul 2020
On the Outsized Importance of Learning Rates in Local Update Methods Zachary B. Charles Jakub Konecný FedML 24 54 0 02 Jul 2020
Shuffle-Exchange Brings Faster: Reduce the Idle Time During Communication for Decentralized Neural Network Training Xiang Yang FedML 18 2 0 01 Jul 2020
FDA3 : Federated Defense Against Adversarial Attacks for Cloud-Based IIoT Applications Yunfei Song Tian Liu Tongquan Wei Xiangfeng Wang Zhe Tao Mingsong Chen 22 48 0 28 Jun 2020