ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2002.02508
  4. Cited By
Differentially Quantized Gradient Methods
v1v2v3v4 (latest)

Differentially Quantized Gradient Methods

IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
6 February 2020
Chung-Yi Lin
V. Kostina
B. Hassibi
    MQ
ArXiv (abs)PDFHTML

Papers citing "Differentially Quantized Gradient Methods"

5 / 5 papers shown
1-Bit FQT: Pushing the Limit of Fully Quantized Training to 1-bit
1-Bit FQT: Pushing the Limit of Fully Quantized Training to 1-bit
Chang Gao
Jianfei Chen
Kang Zhao
Jiaqi Wang
Liping Jing
MQ
236
3
0
26 Aug 2024
Differential error feedback for communication-efficient decentralized
  learning
Differential error feedback for communication-efficient decentralized learning
Roula Nassif
Stefan Vlaski
Marco Carpentiero
Vincenzo Matta
Ali H. Sayed
344
3
0
26 Jun 2024
Compressed Federated Reinforcement Learning with a Generative Model
Compressed Federated Reinforcement Learning with a Generative Model
Ali Beikmohammadi
Sarit Khirirat
Sindri Magnússon
FedML
375
5
0
26 Mar 2024
Temporal Difference Learning with Compressed Updates: Error-Feedback
  meets Reinforcement Learning
Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning
A. Mitra
George J. Pappas
Hamed Hassani
241
14
0
03 Jan 2023
EF-BV: A Unified Theory of Error Feedback and Variance Reduction
  Mechanisms for Biased and Unbiased Compression in Distributed Optimization
EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed OptimizationNeural Information Processing Systems (NeurIPS), 2022
Laurent Condat
Kai Yi
Peter Richtárik
391
26
0
09 May 2022
1
Page 1 of 1