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. 2403.15815
  4. Cited By
Resource-efficient Parallel Split Learning in Heterogeneous Edge
  Computing

Resource-efficient Parallel Split Learning in Heterogeneous Edge Computing

23 March 2024
Mingjin Zhang
Jiannong Cao
Yuvraj Sahni
Xiangchun Chen
Shan Jiang
ArXivPDFHTML

Papers citing "Resource-efficient Parallel Split Learning in Heterogeneous Edge Computing"

7 / 7 papers shown
Title
E-Tree Learning: A Novel Decentralized Model Learning Framework for Edge
  AI
E-Tree Learning: A Novel Decentralized Model Learning Framework for Edge AI
Lei Yang
Yanyan Lu
Jiannong Cao
Jiaming Huang
Mingjin Zhang
50
20
0
04 Aug 2020
SplitFed: When Federated Learning Meets Split Learning
SplitFed: When Federated Learning Meets Split Learning
Chandra Thapa
Pathum Chamikara Mahawaga Arachchige
S. Çamtepe
Lichao Sun
FedML
85
581
0
25 Apr 2020
A Joint Learning and Communications Framework for Federated Learning
  over Wireless Networks
A Joint Learning and Communications Framework for Federated Learning over Wireless Networks
Mingzhe Chen
Zhaohui Yang
Walid Saad
Changchuan Yin
H. Vincent Poor
Shuguang Cui
FedML
64
1,190
0
17 Sep 2019
Accelerating DNN Training in Wireless Federated Edge Learning Systems
Accelerating DNN Training in Wireless Federated Edge Learning Systems
Jinke Ren
Guanding Yu
Guangyao Ding
FedML
48
171
0
23 May 2019
Distributed learning of deep neural network over multiple agents
Distributed learning of deep neural network over multiple agents
O. Gupta
Ramesh Raskar
FedML
OOD
54
603
0
14 Oct 2018
Adaptive Federated Learning in Resource Constrained Edge Computing
  Systems
Adaptive Federated Learning in Resource Constrained Edge Computing Systems
Shiqiang Wang
Tiffany Tuor
Theodoros Salonidis
K. Leung
C. Makaya
T. He
Kevin S. Chan
239
1,704
0
14 Apr 2018
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
380
17,437
0
17 Feb 2016
1