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Global-QSGD: Practical Floatless Quantization for Distributed Learning
  with Theoretical Guarantees

Global-QSGD: Practical Floatless Quantization for Distributed Learning with Theoretical Guarantees

29 May 2023
Jihao Xin
Marco Canini
Peter Richtárik
Samuel Horváth
ArXivPDFHTML

Papers citing "Global-QSGD: Practical Floatless Quantization for Distributed Learning with Theoretical Guarantees"

3 / 3 papers shown
Title
NUQSGD: Provably Communication-efficient Data-parallel SGD via Nonuniform Quantization
Ali Ramezani-Kebrya
Fartash Faghri
Ilya Markov
V. Aksenov
Dan Alistarh
Daniel M. Roy
MQ
59
30
0
28 Apr 2021
IntSGD: Adaptive Floatless Compression of Stochastic Gradients
IntSGD: Adaptive Floatless Compression of Stochastic Gradients
Konstantin Mishchenko
Bokun Wang
D. Kovalev
Peter Richtárik
67
14
0
16 Feb 2021
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
L. V. D. van der Maaten
Kilian Q. Weinberger
PINN
3DV
258
36,371
0
25 Aug 2016
1