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Quantization-Guided Training for Compact TinyML Models

Quantization-Guided Training for Compact TinyML Models

10 March 2021
Sedigh Ghamari
Koray Ozcan
Thu Dinh
A. Melnikov
Juan Carvajal
Jan Ernst
S. Chai
    MQ
ArXiv (abs)PDFHTML

Papers citing "Quantization-Guided Training for Compact TinyML Models"

8 / 8 papers shown
Quantizing Small-Scale State-Space Models for Edge AI
Quantizing Small-Scale State-Space Models for Edge AI
Leo Zhao
Tristan Torchet
Melika Payvand
Laura Kriener
Filippo Moro
MQ
225
3
0
14 Jun 2025
Extreme Compression of Adaptive Neural Images
Extreme Compression of Adaptive Neural Images
Leo Hoshikawa
Marcos V. Conde
Takeshi Ohashi
Atsushi Irie
477
1
0
27 May 2024
LightDepth: A Resource Efficient Depth Estimation Approach for Dealing
  with Ground Truth Sparsity via Curriculum Learning
LightDepth: A Resource Efficient Depth Estimation Approach for Dealing with Ground Truth Sparsity via Curriculum Learning
Fatemeh Karimi
Amir Mehrpanah
Reza Rawassizadeh
295
2
0
16 Nov 2022
Deep learning model compression using network sensitivity and gradients
Deep learning model compression using network sensitivity and gradients
M. Sakthi
N. Yadla
Raj Pawate
226
2
0
11 Oct 2022
Overcoming Oscillations in Quantization-Aware Training
Overcoming Oscillations in Quantization-Aware TrainingInternational Conference on Machine Learning (ICML), 2022
Markus Nagel
Marios Fournarakis
Yelysei Bondarenko
Tijmen Blankevoort
MQ
543
161
0
21 Mar 2022
An Empirical Study of Low Precision Quantization for TinyML
An Empirical Study of Low Precision Quantization for TinyML
Shaojie Zhuo
Hongyu Chen
R. Ramakrishnan
Tommy Chen
Chen Feng
Yi-Rung Lin
Parker Zhang
Liang Shen
MQ
368
24
0
10 Mar 2022
Implicit Neural Representations for Image Compression
Implicit Neural Representations for Image Compression
Yannick Strümpler
Janis Postels
Ren Yang
Luc van Gool
F. Tombari
370
211
0
08 Dec 2021
A TinyML Platform for On-Device Continual Learning with Quantized Latent
  Replays
A TinyML Platform for On-Device Continual Learning with Quantized Latent ReplaysIEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), 2021
Leonardo Ravaglia
Manuele Rusci
D. Nadalini
Alessandro Capotondi
Francesco Conti
Luca Benini
BDL
320
88
0
20 Oct 2021
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