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Doping: A technique for efficient compression of LSTM models using
  sparse structured additive matrices

Doping: A technique for efficient compression of LSTM models using sparse structured additive matrices

14 February 2021
Urmish Thakker
P. Whatmough
Zhi-Gang Liu
Matthew Mattina
Jesse G. Beu
ArXivPDFHTML

Papers citing "Doping: A technique for efficient compression of LSTM models using sparse structured additive matrices"

2 / 2 papers shown
Title
Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training
  Efficiency
Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency
Vithursan Thangarasa
Shreyas Saxena
Abhay Gupta
Sean Lie
25
3
0
21 Mar 2023
Machine Learning for Microcontroller-Class Hardware: A Review
Machine Learning for Microcontroller-Class Hardware: A Review
Swapnil Sayan Saha
S. Sandha
Mani B. Srivastava
19
117
0
29 May 2022
1