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Federated Learning: Strategies for Improving Communication Efficiency

18 October 2016

Dave Bacon

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

50 / 1,868 papers shown

Title
Accumulative Poisoning Attacks on Real-time Data Tianyu Pang Xiao Yang Yinpeng Dong Hang Su Jun Zhu 84 20 0 18 Jun 2021
Towards Heterogeneous Clients with Elastic Federated Learning Zichen Ma Yu Lu Zihan Lu Wenye Li Jinfeng Yi Shuguang Cui FedML 49 3 0 17 Jun 2021
QuantumFed: A Federated Learning Framework for Collaborative Quantum Training Qi Xia Qun Li FedML 113 31 0 16 Jun 2021
Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions Shaashwat Agrawal Sagnik Sarkar Ons Aouedi Gokul Yenduri Kandaraj Piamrat S. Bhattacharya Praveen Kumar Reddy Maddikunta Thippa Reddy Gadekallu 97 262 0 16 Jun 2021
Federated Myopic Community Detection with One-shot Communication Chuyang Ke Jean Honorio FedML 62 5 0 14 Jun 2021
Heterogeneous Federated Learning using Dynamic Model Pruning and Adaptive Gradient Sixing Yu P. Nguyen Ali Anwar Ali Jannesari 83 12 0 13 Jun 2021
Stochastic Alternating Direction Method of Multipliers for Byzantine-Robust Distributed Learning Feng-Shih Lin Weiyu Li Qing Ling FedML 138 6 0 13 Jun 2021
Federated Learning on Non-IID Data: A Survey Hangyu Zhu Jinjin Xu Shiqing Liu Yaochu Jin OOD FedML 121 818 0 12 Jun 2021
Federated Learning with Spiking Neural Networks Yeshwanth Venkatesha Youngeun Kim Leandros Tassiulas Priyadarshini Panda FedML 63 49 0 11 Jun 2021
Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix Maximilian Lam Gu-Yeon Wei David Brooks Vijay Janapa Reddi Michael Mitzenmacher FedML 104 65 0 10 Jun 2021
Next-Gen Machine Learning Supported Diagnostic Systems for Spacecraft Athanasios Vlontzos Gabriel Sutherland Siddha Ganju Frank Soboczenski 53 2 0 10 Jun 2021
Multi-VFL: A Vertical Federated Learning System for Multiple Data and Label Owners Vaikkunth Mugunthan P. Goyal Lalana Kagal FedML 70 9 0 10 Jun 2021
Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning Bokun Wang Zhuoning Yuan Yiming Ying Tianbao Yang FedML 102 11 0 09 Jun 2021
Communication-efficient SGD: From Local SGD to One-Shot Averaging Artin Spiridonoff Alexander Olshevsky I. Paschalidis FedML 112 20 0 09 Jun 2021
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks D. Kovalev Elnur Gasanov Peter Richtárik Alexander Gasnikov 70 44 0 08 Jun 2021
Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh FedML 99 51 0 08 Jun 2021
Widening Access to Applied Machine Learning with TinyML Vijay Janapa Reddi Brian Plancher Susan Kennedy L. Moroney Pete Warden ... Dominic Pajak Dhilan Ramaprasad J. E. Smith Matthew P. Stewart D. Tingley 75 52 0 07 Jun 2021
Preservation of the Global Knowledge by Not-True Distillation in Federated Learning Gihun Lee Minchan Jeong Yongjin Shin Sangmin Bae Se-Young Yun FedML 128 125 0 06 Jun 2021
MURANA: A Generic Framework for Stochastic Variance-Reduced Optimization Laurent Condat Peter Richtárik 77 19 0 06 Jun 2021
FedNL: Making Newton-Type Methods Applicable to Federated Learning M. Safaryan Rustem Islamov Xun Qian Peter Richtárik FedML 104 80 0 05 Jun 2021
SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks Chaoyang He Emir Ceyani Keshav Balasubramanian M. Annavaram Salman Avestimehr FedML 75 52 0 04 Jun 2021
FedCCEA : A Practical Approach of Client Contribution Evaluation for Federated Learning S. K. Shyn Donghee Kim Kwangsu Kim FedML 84 23 0 04 Jun 2021
SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training Enmao Diao Jie Ding Vahid Tarokh FedML 90 76 0 02 Jun 2021
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations Enmao Diao Jie Ding Vahid Tarokh FedML 104 17 0 02 Jun 2021
H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning He Yang 79 28 0 01 Jun 2021
Dynamic Scheduling for Over-the-Air Federated Edge Learning with Energy Constraints Yuxuan Sun Sheng Zhou Z. Niu Deniz Gündüz 114 100 0 31 May 2021
PPT: A Privacy-Preserving Global Model Training Protocol for Federated Learning in P2P Networks Qian Chen Zilong Wang Wenjing Zhang Xiaodong Lin FedML 69 17 0 30 May 2021
Concept drift detection and adaptation for federated and continual learning F. Casado Dylan Lema Marcos F. Criado R. Iglesias Carlos V. Regueiro S. Barro FedML 79 64 0 27 May 2021
Fast Federated Learning by Balancing Communication Trade-Offs Milad Khademi Nori Sangseok Yun Il-Min Kim FedML 87 57 0 23 May 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning Zhuangdi Zhu Junyuan Hong Jiayu Zhou FedML 99 669 0 20 May 2021
Fed-EINI: An Efficient and Interpretable Inference Framework for Decision Tree Ensembles in Federated Learning Xiaolin Chen Shuai Zhou Bei Guan Kai Yang Hao Fao Hu. Wang Yongji Wang FedML 191 16 0 20 May 2021
Federated Learning With Highly Imbalanced Audio Data Marc C. Green Mark D. Plumbley FedML 64 4 0 18 May 2021
DRIVE: One-bit Distributed Mean Estimation S. Vargaftik Ran Ben-Basat Amit Portnoy Gal Mendelson Y. Ben-Itzhak Michael Mitzenmacher OOD FedML 187 55 0 18 May 2021
Differentially Private Federated Knowledge Graphs Embedding Hao Peng Haoran Li Yangqiu Song V. Zheng Jianxin Li FedML 99 85 0 17 May 2021
LocalNewton: Reducing Communication Bottleneck for Distributed Learning Vipul Gupta Avishek Ghosh Michal Derezinski Rajiv Khanna Kannan Ramchandran Michael W. Mahoney 77 13 0 16 May 2021
Node Selection Toward Faster Convergence for Federated Learning on Non-IID Data Hongda Wu Ping Wang FedML 110 143 0 14 May 2021
An Efficient Learning Framework For Federated XGBoost Using Secret Sharing And Distributed Optimization Lunchen Xie Jiaqi Liu Songtao Lu Tsung-Hui Chang Qingjiang Shi FedML 66 38 0 12 May 2021
Separate but Together: Unsupervised Federated Learning for Speech Enhancement from Non-IID Data Efthymios Tzinis Jonah Casebeer Zhepei Wang Paris Smaragdis FedML 68 19 0 11 May 2021
Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates Laizhong Cui Xiaoxin Su Yipeng Zhou Yi Pan FedML 77 37 0 10 May 2021
Stronger Privacy for Federated Collaborative Filtering with Implicit Feedback Lorenzo Minto Moritz Haller Hamed Haddadi B. Livshits FedML 79 74 0 09 May 2021
Loss Tolerant Federated Learning Pengyuan Zhou Pei Fang Pan Hui 51 16 0 08 May 2021
FedGL: Federated Graph Learning Framework with Global Self-Supervision Chuan Chen Weibo Hu Ziyue Xu Zibin Zheng FedML 69 59 0 07 May 2021
Density-Aware Federated Imitation Learning for Connected and Automated Vehicles with Unsignalized Intersection Tianhao Wu Mingzhi Jiang Yinhui Han Zheng Yuan Lin Zhang 23 2 0 05 May 2021
OCTOPUS: Overcoming Performance andPrivatization Bottlenecks in Distributed Learning Shuo Wang Surya Nepal Kristen Moore M. Grobler Carsten Rudolph A. Abuadbba FedML 79 8 0 03 May 2021
Personalized Federated Learning by Structured and Unstructured Pruning under Data Heterogeneity Saeed Vahidian Mahdi Morafah Bill Lin 115 61 0 02 May 2021
Cluster-driven Graph Federated Learning over Multiple Domains Debora Caldarola Massimiliano Mancini Fabio Galasso Marco Ciccone Emanuele Rodolà Barbara Caputo FedML 125 86 0 29 Apr 2021
Privacy-Preserving Federated Learning on Partitioned Attributes Shuang Zhang Liyao Xiang Xi Yu Pengzhi Chu Yingqi Chen Chen Cen L. Wang FedML 128 2 0 29 Apr 2021
From Distributed Machine Learning to Federated Learning: A Survey Ji Liu Jizhou Huang Yang Zhou Xuhong Li Shilei Ji Haoyi Xiong Dejing Dou FedML OOD 153 263 0 29 Apr 2021
End-to-End Speech Recognition from Federated Acoustic Models Yan Gao Titouan Parcollet Salah Zaiem Javier Fernandez-Marques Pedro Porto Buarque de Gusmão Daniel J. Beutel Nicholas D. Lane 103 44 0 29 Apr 2021
Pronto: Federated Task Scheduling Andreas Grammenos Evangelia Kalyvianaki Peter R. Pietzuch FedML 37 1 0 27 Apr 2021