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. 2305.13503
  4. Cited By
Asynchronous Multi-Model Dynamic Federated Learning over Wireless
  Networks: Theory, Modeling, and Optimization

Asynchronous Multi-Model Dynamic Federated Learning over Wireless Networks: Theory, Modeling, and Optimization

22 May 2023
Zhangyu Chang
Seyyedali Hosseinalipour
M. Chiang
Christopher G. Brinton
ArXivPDFHTML

Papers citing "Asynchronous Multi-Model Dynamic Federated Learning over Wireless Networks: Theory, Modeling, and Optimization"

18 / 18 papers shown
Title
Delay-Aware Hierarchical Federated Learning
Delay-Aware Hierarchical Federated Learning
F. Lin
Seyyedali Hosseinalipour
Nicolò Michelusi
Christopher G. Brinton
FedML
53
11
0
22 Mar 2023
Resource-Aware Asynchronous Online Federated Learning for Nonlinear
  Regression
Resource-Aware Asynchronous Online Federated Learning for Nonlinear Regression
François Gauthier
Vinay Chakravarthi Gogineni
Stefan Werner
Yih-Fang Huang
A. Kuh
FedML
45
9
0
27 Nov 2021
Successive Convex Approximation Based Off-Policy Optimization for
  Constrained Reinforcement Learning
Successive Convex Approximation Based Off-Policy Optimization for Constrained Reinforcement Learning
Chang Tian
An Liu
Guang-Li Huang
Wu Luo
35
12
0
26 May 2021
Semi-Decentralized Federated Learning with Cooperative D2D Local Model
  Aggregations
Semi-Decentralized Federated Learning with Cooperative D2D Local Model Aggregations
F. Lin
Seyyedali Hosseinalipour
Sheikh Shams Azam
Christopher G. Brinton
Nicolò Michelusi
FedML
68
112
0
18 Mar 2021
Federated Learning on Non-IID Data Silos: An Experimental Study
Federated Learning on Non-IID Data Silos: An Experimental Study
Yue Liu
Yiqun Diao
Quan Chen
Bingsheng He
FedML
OOD
151
981
0
03 Feb 2021
Device Sampling for Heterogeneous Federated Learning: Theory,
  Algorithms, and Implementation
Device Sampling for Heterogeneous Federated Learning: Theory, Algorithms, and Implementation
Su Wang
Mengyuan Lee
Seyyedali Hosseinalipour
Roberto Morabito
M. Chiang
Christopher G. Brinton
FedML
114
112
0
04 Jan 2021
Toward Multiple Federated Learning Services Resource Sharing in Mobile
  Edge Networks
Toward Multiple Federated Learning Services Resource Sharing in Mobile Edge Networks
Minh N. H. Nguyen
N. H. Tran
Y. Tun
Zhu Han
Choong Seon Hong
FedML
67
50
0
25 Nov 2020
Dynamic Federated Learning
Dynamic Federated Learning
Elsa Rizk
Stefan Vlaski
Ali H. Sayed
FedML
84
25
0
20 Feb 2020
Personalized Federated Learning: A Meta-Learning Approach
Personalized Federated Learning: A Meta-Learning Approach
Alireza Fallah
Aryan Mokhtari
Asuman Ozdaglar
FedML
152
568
0
19 Feb 2020
Convergence of Update Aware Device Scheduling for Federated Learning at
  the Wireless Edge
Convergence of Update Aware Device Scheduling for Federated Learning at the Wireless Edge
M. Amiri
Deniz Gunduz
Sanjeev R. Kulkarni
H. Vincent Poor
115
173
0
28 Jan 2020
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task
  Optimization under Privacy Constraints
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
Felix Sattler
K. Müller
Wojciech Samek
FedML
143
1,003
0
04 Oct 2019
Local SGD Converges Fast and Communicates Little
Local SGD Converges Fast and Communicates Little
Sebastian U. Stich
FedML
170
1,061
0
24 May 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
245
1,706
0
14 Apr 2018
On the convergence properties of a $K$-step averaging stochastic
  gradient descent algorithm for nonconvex optimization
On the convergence properties of a KKK-step averaging stochastic gradient descent algorithm for nonconvex optimization
Fan Zhou
Guojing Cong
129
234
0
03 Aug 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
297
4,643
0
18 Oct 2016
Asynchronous Stochastic Gradient Descent with Delay Compensation
Asynchronous Stochastic Gradient Descent with Delay Compensation
Shuxin Zheng
Qi Meng
Taifeng Wang
Wei Chen
Nenghai Yu
Zhiming Ma
Tie-Yan Liu
98
314
0
27 Sep 2016
Parallel and Distributed Methods for Nonconvex Optimization--Part II:
  Applications
Parallel and Distributed Methods for Nonconvex Optimization--Part II: Applications
G. Scutari
F. Facchinei
Lorenzo Lampariello
Peiran Song
Stefania Sardellitti
42
258
0
15 Jan 2016
Distributed Optimization with Arbitrary Local Solvers
Distributed Optimization with Arbitrary Local Solvers
Chenxin Ma
Jakub Konecný
Martin Jaggi
Virginia Smith
Michael I. Jordan
Peter Richtárik
Martin Takáč
85
198
0
13 Dec 2015
1