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
MURANA: A Generic Framework for Stochastic Variance-Reduced Optimization Laurent Condat Peter Richtárik 12 19 0 06 Jun 2021
FedNL: Making Newton-Type Methods Applicable to Federated Learning M. Safaryan Rustem Islamov Xun Qian Peter Richtárik FedML 33 78 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 25 50 0 04 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
SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training Enmao Diao Jie Ding Vahid Tarokh FedML 30 73 0 02 Jun 2021
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations Enmao Diao Jie Ding Vahid Tarokh FedML 30 17 0 02 Jun 2021
H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning He Yang 22 27 0 01 Jun 2021
Dynamic Scheduling for Over-the-Air Federated Edge Learning with Energy Constraints Yuxuan Sun Sheng Zhou Z. Niu Deniz Gündüz 27 93 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 33 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 13 63 0 27 May 2021
Fast Federated Learning by Balancing Communication Trade-Offs Milad Khademi Nori Sangseok Yun Il-Min Kim FedML 32 53 0 23 May 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning Zhuangdi Zhu Junyuan Hong Jiayu Zhou FedML 32 633 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 39 16 0 20 May 2021
Federated Learning With Highly Imbalanced Audio Data Marc C. Green Mark D. Plumbley FedML 35 3 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 86 52 0 18 May 2021
Differentially Private Federated Knowledge Graphs Embedding Hao Peng Haoran Li Yangqiu Song V. Zheng Jianxin Li FedML 36 80 0 17 May 2021
LocalNewton: Reducing Communication Bottleneck for Distributed Learning Vipul Gupta Avishek Ghosh Michal Derezinski Rajiv Khanna Kannan Ramchandran Michael W. Mahoney 38 12 0 16 May 2021
Node Selection Toward Faster Convergence for Federated Learning on Non-IID Data Hongda Wu Ping Wang FedML 34 135 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 26 37 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 32 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 38 36 0 10 May 2021
Stronger Privacy for Federated Collaborative Filtering with Implicit Feedback Lorenzo Minto Moritz Haller Hamed Haddadi B. Livshits FedML 6 74 0 09 May 2021
Loss Tolerant Federated Learning Pengyuan Zhou Pei Fang Pan Hui 29 16 0 08 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
Density-Aware Federated Imitation Learning for Connected and Automated Vehicles with Unsignalized Intersection Tianhao Wu Mingzhi Jiang Yinhui Han Zheng Yuan Lin Zhang 13 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 45 8 0 03 May 2021
Personalized Federated Learning by Structured and Unstructured Pruning under Data Heterogeneity Saeed Vahidian Mahdi Morafah Bill Lin 67 58 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 19 83 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 28 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 56 244 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 28 43 0 29 Apr 2021
Pronto: Federated Task Scheduling Andreas Grammenos Evangelia Kalyvianaki Peter R. Pietzuch FedML 22 1 0 27 Apr 2021
Confined Gradient Descent: Privacy-preserving Optimization for Federated Learning Yanjun Zhang Guangdong Bai Xue Li Surya Nepal R. Ko FedML 23 2 0 27 Apr 2021
Multi-resource allocation for federated settings: A non-homogeneous Markov chain model Syed Eqbal Alam Fabian R. Wirth Jia Yuan Yu 19 0 0 26 Apr 2021
Communication-Efficient Federated Learning with Dual-Side Low-Rank Compression Zhefeng Qiao Xianghao Yu Jun Zhang Khaled B. Letaief FedML 48 19 0 26 Apr 2021
Wireless Federated Learning (WFL) for 6G Networks -- Part II: The Compute-then-Transmit NOMA Paradigm Pavlos S. Bouzinis P. Diamantoulakis G. Karagiannidis 33 37 0 24 Apr 2021
Wireless Federated Learning (WFL) for 6G Networks -- Part I: Research Challenges and Future Trends Pavlos S. Bouzinis P. Diamantoulakis G. Karagiannidis 23 48 0 24 Apr 2021
Partitioning sparse deep neural networks for scalable training and inference G. Demirci Hakan Ferhatosmanoglu 25 11 0 23 Apr 2021
Leveraging Sharing Communities to Achieve Federated Learning for Cybersecurity Frank W. Bentrem Michael A. Corsello Joshua J. Palm FedML 21 0 0 23 Apr 2021
Gradient Masked Federated Optimization Irene Tenison Sreya Francis Irina Rish FedML 28 2 0 21 Apr 2021
See through Gradients: Image Batch Recovery via GradInversion Hongxu Yin Arun Mallya Arash Vahdat J. Álvarez Jan Kautz Pavlo Molchanov FedML 25 462 0 15 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 45 43 0 15 Apr 2021
Personalized Semi-Supervised Federated Learning for Human Activity Recognition Riccardo Presotto Gabriele Civitarese Claudio Bettini 34 65 0 15 Apr 2021
Efficient Ring-topology Decentralized Federated Learning with Deep Generative Models for Industrial Artificial Intelligent Zhao Wang Yifan Hu Jun Xiao Chao-Xiang Wu AI4CE 24 11 0 15 Apr 2021
Resource Rationing for Wireless Federated Learning: Concept, Benefits, and Challenges Cong Shen Jie Xu Sihui Zheng Xiang Chen 17 20 0 14 Apr 2021
Privacy-preserving Federated Learning based on Multi-key Homomorphic Encryption Jing Ma Si-Ahmed Naas S. Sigg X. Lyu 29 245 0 14 Apr 2021
BROADCAST: Reducing Both Stochastic and Compression Noise to Robustify Communication-Efficient Federated Learning He Zhu Qing Ling FedML AAML 24 11 0 14 Apr 2021
Device-Cloud Collaborative Learning for Recommendation Jiangchao Yao Feng Wang Kunyang Jia Bo Han Jingren Zhou Hongxia Yang 30 60 0 14 Apr 2021
Practical Defences Against Model Inversion Attacks for Split Neural Networks Tom Titcombe A. Hall Pavlos Papadopoulos Daniele Romanini FedML 35 58 0 12 Apr 2021
Applications of physics-informed scientific machine learning in subsurface science: A survey A. Sun H. Yoon C. Shih Zhi Zhong AI4CE 29 10 0 10 Apr 2021