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. 2210.00486
  4. Cited By
pMPL: A Robust Multi-Party Learning Framework with a Privileged Party

pMPL: A Robust Multi-Party Learning Framework with a Privileged Party

2 October 2022
Lushan Song
Jiaxuan Wang
Zhexuan Wang
Xinyu Tu
Guopeng Lin
Wenqiang Ruan
Haoqi Wu
Wei Han
ArXivPDFHTML

Papers citing "pMPL: A Robust Multi-Party Learning Framework with a Privileged Party"

1 / 1 papers shown
Title
HawkEye: Statically and Accurately Profiling the Communication Cost of Models in Multi-party Learning
HawkEye: Statically and Accurately Profiling the Communication Cost of Models in Multi-party Learning
Wenqiang Ruan
Xin Lin
Ruisheng Zhou
Guopeng Lin
Shui Yu
Weili Han
55
0
0
16 Feb 2025
1