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. 2407.13703
  4. Cited By
Energy-Efficient Channel Decoding for Wireless Federated Learning:
  Convergence Analysis and Adaptive Design

Energy-Efficient Channel Decoding for Wireless Federated Learning: Convergence Analysis and Adaptive Design

26 June 2024
Linping Qu
Yuyi Mao
Shenghui Song
Chi-Ying Tsui
ArXivPDFHTML

Papers citing "Energy-Efficient Channel Decoding for Wireless Federated Learning: Convergence Analysis and Adaptive Design"

4 / 4 papers shown
Title
FedDQ: Communication-Efficient Federated Learning with Descending
  Quantization
FedDQ: Communication-Efficient Federated Learning with Descending Quantization
Linping Qu
Shenghui Song
Chi-Ying Tsui
FedML
MQ
81
26
0
05 Oct 2021
Federated Learning over Noisy Channels: Convergence Analysis and Design
  Examples
Federated Learning over Noisy Channels: Convergence Analysis and Design Examples
Xizixiang Wei
Cong Shen
FedML
36
15
0
06 Jan 2021
Device Heterogeneity in Federated Learning: A Superquantile Approach
Device Heterogeneity in Federated Learning: A Superquantile Approach
Yassine Laguel
Krishna Pillutla
J. Malick
Zaïd Harchaoui
FedML
19
22
0
25 Feb 2020
FedPAQ: A Communication-Efficient Federated Learning Method with
  Periodic Averaging and Quantization
FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization
Amirhossein Reisizadeh
Aryan Mokhtari
Hamed Hassani
Ali Jadbabaie
Ramtin Pedarsani
FedML
157
758
0
28 Sep 2019
1