Federated Learning: Strategies for Improving Communication Efficiency

18 October 2016

Dave Bacon

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

50 / 1,848 papers shown

Title
From Local SGD to Local Fixed-Point Methods for Federated Learning Grigory Malinovsky D. Kovalev Elnur Gasanov Laurent Condat Peter Richtárik FedML 27 115 0 03 Apr 2020
A Blockchain-based Decentralized Federated Learning Framework with Committee Consensus Yuzheng Li Chuan Chen Nan Liu Huawei Huang Zibin Zheng Qiang Yan FedML 31 397 0 02 Apr 2020
Assisted Learning: A Framework for Multi-Organization Learning Xun Xian Xinran Wang Jie Ding R. Ghanadan FedML 13 1 0 01 Apr 2020
Scheduling for Cellular Federated Edge Learning with Importance and Channel Awareness Jinke Ren Yinghui He Dingzhu Wen Guanding Yu Kaibin Huang Dongning Guo 36 193 0 01 Apr 2020
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies David Enthoven Zaid Al-Ars FedML 60 50 0 01 Apr 2020
Increasing negotiation performance at the edge of the network Sam Vente Angelika Kimmig Alun D. Preece Federico Cerutti 8 4 0 30 Mar 2020
Semi-Federated Learning Zhikun Chen Daofeng Li Mingde Zhao Sihai Zhang Jinkang Zhu FedML 8 18 0 28 Mar 2020
Edge Intelligence: Architectures, Challenges, and Applications Dianlei Xu Tong Li Yong Li Xiang Su Sasu Tarkoma Tao Jiang Jon Crowcroft Pan Hui 41 29 0 26 Mar 2020
The Internet of Things as a Deep Neural Network Rong Du Sindri Magnússon Carlo Fischione 9 7 0 23 Mar 2020
Dynamic Sampling and Selective Masking for Communication-Efficient Federated Learning Shaoxiong Ji Wenqi Jiang A. Walid Xue Li FedML 28 66 0 21 Mar 2020
Privacy-preserving Traffic Flow Prediction: A Federated Learning Approach Yi Liu James J. Q. Yu Jiawen Kang Dusit Niyato Shuyu Zhang AI4TS 19 442 0 19 Mar 2020
A Compressive Sensing Approach for Federated Learning over Massive MIMO Communication Systems Yo-Seb Jeon M. Amiri Jun Li H. Vincent Poor 30 9 0 18 Mar 2020
Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training? Sharif Abuadbba Kyuyeon Kim Minki Kim Chandra Thapa S. Çamtepe Yansong Gao Hyoungshick Kim Surya Nepal FedML 8 122 0 16 Mar 2020
Policy-Based Federated Learning Kleomenis Katevas Eugene Bagdasaryan J. Waterman Mohamad Mounir Safadieh Eleanor Birrell Hamed Haddadi D. Estrin 19 0 0 14 Mar 2020
Machine Learning on Volatile Instances Xiaoxi Zhang Jianyu Wang Gauri Joshi Carlee Joe-Wong 15 25 0 12 Mar 2020
Communication-efficient Variance-reduced Stochastic Gradient Descent H. S. Ghadikolaei Sindri Magnússon 4 3 0 10 Mar 2020
Communication-Efficient Distributed Deep Learning: A Comprehensive Survey Zhenheng Tang S. Shi Wei Wang Bo-wen Li Xiaowen Chu 21 48 0 10 Mar 2020
FedLoc: Federated Learning Framework for Data-Driven Cooperative Localization and Location Data Processing Feng Yin Zhidi Lin Yue Xu Qinglei Kong Deshi Li Sergios Theodoridis Shuguang Cui Cui FedML 14 4 0 08 Mar 2020
Trends and Advancements in Deep Neural Network Communication Felix Sattler Thomas Wiegand Wojciech Samek GNN 33 9 0 06 Mar 2020
Decentralized SGD with Over-the-Air Computation Emre Ozfatura Stefano Rini Deniz Gunduz 13 38 0 06 Mar 2020
Practical Privacy Preserving POI Recommendation Chaochao Chen Jun Zhou Bingzhe Wu W. Fang Li Wang Yuan Qi Xiaolin Zheng 6 67 0 05 Mar 2020
Real-time Federated Evolutionary Neural Architecture Search Hangyu Zhu Yaochu Jin FedML 147 71 0 04 Mar 2020
Privacy-preserving Learning via Deep Net Pruning Yangsibo Huang Yushan Su S. S. Ravi Zhao Song Sanjeev Arora Keqin Li MLT 14 16 0 04 Mar 2020
FLAME: A Self-Adaptive Auto-labeling System for Heterogeneous Mobile Processors Jie Liu Jiawen Liu Zhen Xie Dong Li 24 5 0 03 Mar 2020
Marketplace for AI Models Abhishek Kumar Benjamin Finley Tristan Braud Sasu Tarkoma Pan Hui DiffM 10 14 0 03 Mar 2020
Buffered Asynchronous SGD for Byzantine Learning Yi-Rui Yang Wu-Jun Li FedML 29 5 0 02 Mar 2020
User-Level Privacy-Preserving Federated Learning: Analysis and Performance Optimization Kang Wei Jun Li Ming Ding Chuan Ma Hang Su Bo-Wen Zhang H. Vincent Poor FedML 25 11 0 29 Feb 2020
Federated Over-Air Subspace Tracking from Incomplete and Corrupted Data Praneeth Narayanamurthy Namrata Vaswani Aditya Ramamoorthy 14 10 0 28 Feb 2020
On Biased Compression for Distributed Learning Aleksandr Beznosikov Samuel Horváth Peter Richtárik M. Safaryan 8 183 0 27 Feb 2020
An On-Device Federated Learning Approach for Cooperative Model Update between Edge Devices Rei Ito Mineto Tsukada Hiroki Matsutani FedML 24 7 0 27 Feb 2020
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization Zhize Li D. Kovalev Xun Qian Peter Richtárik FedML AI4CE 29 135 0 26 Feb 2020
HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning Siqi Luo Xu Chen Qiong Wu Zhi Zhou Shuai Yu FedML 33 339 0 26 Feb 2020
Device Heterogeneity in Federated Learning: A Superquantile Approach Yassine Laguel Krishna Pillutla J. Malick Zaïd Harchaoui FedML 40 22 0 25 Feb 2020
Optimal Gradient Quantization Condition for Communication-Efficient Distributed Training An Xu Zhouyuan Huo Heng-Chiao Huang MQ 13 6 0 25 Feb 2020
Distributed Ledger for Provenance Tracking of Artificial Intelligence Assets Philipp Lüthi Thibault Gagnaux Marcel Gygli 6 14 0 25 Feb 2020
Three Approaches for Personalization with Applications to Federated Learning Yishay Mansour M. Mohri Jae Hun Ro A. Suresh FedML 45 565 0 25 Feb 2020
Federated Learning for Resource-Constrained IoT Devices: Panoramas and State-of-the-art Ahmed Imteaj Urmish Thakker Shiqiang Wang Jian Li M. Amini 8 59 0 25 Feb 2020
Learning Structured Distributions From Untrusted Batches: Faster and Simpler Sitan Chen Jungshian Li Ankur Moitra 8 18 0 24 Feb 2020
An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning Xue Yang Yan Feng Weijun Fang Jun Shao Xiaohu Tang Shutao Xia Rongxing Lu FedML AAML 21 44 0 23 Feb 2020
Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection Zhenheng Tang S. Shi X. Chu FedML 21 57 0 22 Feb 2020
Communication-Efficient Edge AI: Algorithms and Systems Yuanming Shi Kai Yang Tao Jiang Jun Zhang Khaled B. Letaief GNN 20 326 0 22 Feb 2020
Uncertainty Principle for Communication Compression in Distributed and Federated Learning and the Search for an Optimal Compressor M. Safaryan Egor Shulgin Peter Richtárik 32 60 0 20 Feb 2020
Dynamic Federated Learning Elsa Rizk Stefan Vlaski Ali H. Sayed FedML 22 25 0 20 Feb 2020
Federated pretraining and fine tuning of BERT using clinical notes from multiple silos Dianbo Liu Timothy A. Miller AI4MH 30 34 0 20 Feb 2020
Personalized Federated Learning: A Meta-Learning Approach Alireza Fallah Aryan Mokhtari Asuman Ozdaglar FedML 36 561 0 19 Feb 2020
Federated Extra-Trees with Privacy Preserving Yang Liu Mingxi Chen Wenxi Zhang Junbo Zhang Yu Zheng FedML 28 3 0 18 Feb 2020
Federated Neural Architecture Search Jinliang Yuan Mengwei Xu Yuxin Zhao Kaigui Bian Gang Huang Xuanzhe Liu Shangguang Wang FedML 19 35 0 15 Feb 2020
Optimal Pricing of Internet of Things: A Machine Learning Approach Mohammad Abu Alsheikh D. Hoang Dusit Niyato Derek Leong Ping Wang Zhu Han 8 17 0 14 Feb 2020
Robustness analytics to data heterogeneity in edge computing Jia Qian Lars Kai Hansen Xenofon Fafoutis Prayag Tiwari Hari Mohan Pandey FedML 16 5 0 12 Feb 2020
Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning Jinhyun So Başak Güler A. Avestimehr FedML 27 289 0 11 Feb 2020