ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2104.14362
  4. Cited By
From Distributed Machine Learning to Federated Learning: A Survey
v1v2v3v4 (latest)

From Distributed Machine Learning to Federated Learning: A Survey

29 April 2021
Ji Liu
Jizhou Huang
Yang Zhou
Xuhong Li
Shilei Ji
Haoyi Xiong
Dejing Dou
    FedMLOOD
ArXiv (abs)PDFHTML

Papers citing "From Distributed Machine Learning to Federated Learning: A Survey"

17 / 117 papers shown
Title
Exploiting Unintended Feature Leakage in Collaborative Learning
Exploiting Unintended Feature Leakage in Collaborative Learning
Luca Melis
Congzheng Song
Emiliano De Cristofaro
Vitaly Shmatikov
FedML
155
1,478
0
10 May 2018
Differentially Private Federated Learning: A Client Level Perspective
Differentially Private Federated Learning: A Client Level Perspective
Robin C. Geyer
T. Klein
Moin Nabi
FedML
133
1,297
0
20 Dec 2017
Private federated learning on vertically partitioned data via entity
  resolution and additively homomorphic encryption
Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption
Stephen Hardy
Wilko Henecka
Hamish Ivey-Law
Richard Nock
Giorgio Patrini
Guillaume Smith
Brian Thorne
FedML
68
536
0
29 Nov 2017
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
479
20,225
0
30 Oct 2017
Optimized Broadcast for Deep Learning Workloads on Dense-GPU InfiniBand
  Clusters: MPI or NCCL?
Optimized Broadcast for Deep Learning Workloads on Dense-GPU InfiniBand Clusters: MPI or NCCL?
A. A. Awan
Ching-Hsiang Chu
Hari Subramoni
D. Panda
GNN
80
46
0
28 Jul 2017
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case
  Study for Decentralized Parallel Stochastic Gradient Descent
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent
Xiangru Lian
Ce Zhang
Huan Zhang
Cho-Jui Hsieh
Wei Zhang
Ji Liu
50
1,233
0
25 May 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep
  Learning
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning
Briland Hitaj
G. Ateniese
Fernando Perez-Cruz
FedML
120
1,404
0
24 Feb 2017
Federated Learning: Strategies for Improving Communication Efficiency
Federated Learning: Strategies for Improving Communication Efficiency
Jakub Konecný
H. B. McMahan
Felix X. Yu
Peter Richtárik
A. Suresh
Dave Bacon
FedML
306
4,649
0
18 Oct 2016
Decentralized Collaborative Learning of Personalized Models over
  Networks
Decentralized Collaborative Learning of Personalized Models over Networks
Paul Vanhaesebrouck
A. Bellet
Marc Tommasi
FedML
52
231
0
17 Oct 2016
Deep Learning with Differential Privacy
Deep Learning with Differential Privacy
Martín Abadi
Andy Chu
Ian Goodfellow
H. B. McMahan
Ilya Mironov
Kunal Talwar
Li Zhang
FedMLSyDa
216
6,155
0
01 Jul 2016
Distributed TensorFlow with MPI
Distributed TensorFlow with MPI
Abhinav Vishnu
Charles Siegel
J. Daily
51
39
0
07 Mar 2016
Communication-Efficient Learning of Deep Networks from Decentralized
  Data
Communication-Efficient Learning of Deep Networks from Decentralized Data
H. B. McMahan
Eider Moore
Daniel Ramage
S. Hampson
Blaise Agüera y Arcas
FedML
406
17,559
0
17 Feb 2016
Secure Multi-Party Computation Based Privacy Preserving Extreme Learning
  Machine Algorithm Over Vertically Distributed Data
Secure Multi-Party Computation Based Privacy Preserving Extreme Learning Machine Algorithm Over Vertically Distributed Data
Ferhat Ozgur Catak
60
12
0
09 Feb 2016
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
280
19,107
0
20 Dec 2014
Hacking Smart Machines with Smarter Ones: How to Extract Meaningful Data
  from Machine Learning Classifiers
Hacking Smart Machines with Smarter Ones: How to Extract Meaningful Data from Machine Learning Classifiers
G. Ateniese
G. Felici
L. Mancini
A. Spognardi
Antonio Villani
Domenico Vitali
84
462
0
19 Jun 2013
A Survey on Multi-view Learning
A Survey on Multi-view Learning
Chang Xu
Dacheng Tao
Chao Xu
AI4TS
114
1,132
0
20 Apr 2013
Diffusion Adaptation Strategies for Distributed Optimization and
  Learning over Networks
Diffusion Adaptation Strategies for Distributed Optimization and Learning over Networks
Jianshu Chen
Ali H. Sayed
99
655
0
31 Oct 2011
Previous
123