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Quantization and Training of Neural Networks for Efficient
  Integer-Arithmetic-Only Inference

Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

15 December 2017
Benoit Jacob
S. Kligys
Bo Chen
Menglong Zhu
Matthew Tang
Andrew G. Howard
Hartwig Adam
Dmitry Kalenichenko
    MQ
ArXiv (abs)PDFHTML

Papers citing "Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference"

50 / 1,298 papers shown
Title
Binary Neural Networks as a general-propose compute paradigm for
  on-device computer vision
Binary Neural Networks as a general-propose compute paradigm for on-device computer vision
Guhong Nie
Lirui Xiao
Menglong Zhu
Dongliang Chu
Yue-Hong Shen
Peng Li
Kan Yang
Li Du
Bo Chen Dji Innovations Inc
MQ
72
6
0
08 Feb 2022
Energy awareness in low precision neural networks
Energy awareness in low precision neural networks
Nurit Spingarn-Eliezer
Ron Banner
Elad Hoffer
Hilla Ben-Yaacov
T. Michaeli
139
0
0
06 Feb 2022
The Ecological Footprint of Neural Machine Translation Systems
The Ecological Footprint of Neural Machine Translation Systems
D. Shterionov
Eva Vanmassenhove
73
3
0
04 Feb 2022
Few-Bit Backward: Quantized Gradients of Activation Functions for Memory
  Footprint Reduction
Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction
Georgii Sergeevich Novikov
Daniel Bershatsky
Julia Gusak
Alex Shonenkov
Denis Dimitrov
Ivan Oseledets
MQ
88
17
0
01 Feb 2022
Neural-PIM: Efficient Processing-In-Memory with Neural Approximation of
  Peripherals
Neural-PIM: Efficient Processing-In-Memory with Neural Approximation of Peripherals
Weidong Cao
Yilong Zhao
Adith Boloor
Yinhe Han
Xuan Zhang
Li Jiang
83
20
0
30 Jan 2022
Post-training Quantization for Neural Networks with Provable Guarantees
Post-training Quantization for Neural Networks with Provable Guarantees
Jinjie Zhang
Yixuan Zhou
Rayan Saab
MQ
73
34
0
26 Jan 2022
AutoMC: Automated Model Compression based on Domain Knowledge and
  Progressive search strategy
AutoMC: Automated Model Compression based on Domain Knowledge and Progressive search strategy
Chunnan Wang
Hongzhi Wang
Xiangyu Shi
51
0
0
24 Jan 2022
Neural Network Quantization with AI Model Efficiency Toolkit (AIMET)
Neural Network Quantization with AI Model Efficiency Toolkit (AIMET)
S. Siddegowda
Marios Fournarakis
Markus Nagel
Tijmen Blankevoort
Chirag I. Patel
Abhijit Khobare
MQ
70
34
0
20 Jan 2022
HEAM: High-Efficiency Approximate Multiplier Optimization for Deep
  Neural Networks
HEAM: High-Efficiency Approximate Multiplier Optimization for Deep Neural Networks
Su Zheng
Zhen Li
Yao Lu
Jingbo Gao
Jide Zhang
Lingli Wang
31
6
0
20 Jan 2022
Q-ViT: Fully Differentiable Quantization for Vision Transformer
Q-ViT: Fully Differentiable Quantization for Vision Transformer
Zhexin Li
Tong Yang
Peisong Wang
Jian Cheng
ViTMQ
90
42
0
19 Jan 2022
Recursive Least Squares for Training and Pruning Convolutional Neural
  Networks
Recursive Least Squares for Training and Pruning Convolutional Neural Networks
Tianzong Yu
Chunyuan Zhang
Yuan Wang
Meng-tao Ma
Qingwei Song
69
1
0
13 Jan 2022
Target Chase, Wall Building, and Fire Fighting: Autonomous UAVs of Team
  NimbRo at MBZIRC 2020
Target Chase, Wall Building, and Fire Fighting: Autonomous UAVs of Team NimbRo at MBZIRC 2020
Marius Beul
Max Schwarz
Jan Quenzel
Malte Splietker
S. Bultmann
...
Patrick Lowin
Bruno Scheider
M. Schreiber
Finn Suberkrub
Sven Behnke
64
3
0
11 Jan 2022
GhostNets on Heterogeneous Devices via Cheap Operations
GhostNets on Heterogeneous Devices via Cheap Operations
Kai Han
Yunhe Wang
Chang Xu
Jianyuan Guo
Chunjing Xu
Enhua Wu
Qi Tian
78
108
0
10 Jan 2022
Glance and Focus Networks for Dynamic Visual Recognition
Glance and Focus Networks for Dynamic Visual Recognition
Gao Huang
Yulin Wang
Kangchen Lv
Haojun Jiang
Wenhui Huang
Pengfei Qi
S. Song
3DH
150
50
0
09 Jan 2022
PocketNN: Integer-only Training and Inference of Neural Networks via
  Direct Feedback Alignment and Pocket Activations in Pure C++
PocketNN: Integer-only Training and Inference of Neural Networks via Direct Feedback Alignment and Pocket Activations in Pure C++
Jae-Su Song
Fangzhen Lin
MQ
37
7
0
08 Jan 2022
BottleFit: Learning Compressed Representations in Deep Neural Networks
  for Effective and Efficient Split Computing
BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing
Yoshitomo Matsubara
Davide Callegaro
Sameer Singh
Marco Levorato
Francesco Restuccia
64
41
0
07 Jan 2022
The Effect of Model Compression on Fairness in Facial Expression
  Recognition
The Effect of Model Compression on Fairness in Facial Expression Recognition
Samuil Stoychev
Hatice Gunes
CVBM
131
19
0
05 Jan 2022
Problem-dependent attention and effort in neural networks with
  applications to image resolution and model selection
Problem-dependent attention and effort in neural networks with applications to image resolution and model selection
Chris Rohlfs
81
4
0
05 Jan 2022
A Heterogeneous In-Memory Computing Cluster For Flexible End-to-End
  Inference of Real-World Deep Neural Networks
A Heterogeneous In-Memory Computing Cluster For Flexible End-to-End Inference of Real-World Deep Neural Networks
Angelo Garofalo
G. Ottavi
Francesco Conti
G. Karunaratne
I. Boybat
Luca Benini
D. Rossi
78
34
0
04 Jan 2022
Implicit Neural Video Compression
Implicit Neural Video Compression
Yunfan Zhang
T. V. Rozendaal
Johann Brehmer
Markus Nagel
Taco S. Cohen
103
58
0
21 Dec 2021
Elastic-Link for Binarized Neural Network
Elastic-Link for Binarized Neural Network
Jie Hu
Ziheng Wu
Vince Tan
Zhilin Lu
Mengze Zeng
Enhua Wu
MQ
60
6
0
19 Dec 2021
Torch.fx: Practical Program Capture and Transformation for Deep Learning
  in Python
Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python
James K. Reed
Zach DeVito
Horace He
Ansley Ussery
Jason Ansel
CLIP
50
49
0
15 Dec 2021
N3H-Core: Neuron-designed Neural Network Accelerator via FPGA-based
  Heterogeneous Computing Cores
N3H-Core: Neuron-designed Neural Network Accelerator via FPGA-based Heterogeneous Computing Cores
Yu Gong
Zhihang Xu
Zhezhi He
Weifeng Zhang
Xiaobing Tu
Xiaoyao Liang
Li Jiang
56
13
0
15 Dec 2021
Synapse Compression for Event-Based Convolutional-Neural-Network
  Accelerators
Synapse Compression for Event-Based Convolutional-Neural-Network Accelerators
Lennart Bamberg
Arash Pourtaherian
Luc Waeijen
A. Chahar
Orlando Moreira
86
5
0
13 Dec 2021
Illumination and Temperature-Aware Multispectral Networks for
  Edge-Computing-Enabled Pedestrian Detection
Illumination and Temperature-Aware Multispectral Networks for Edge-Computing-Enabled Pedestrian Detection
Yifan Zhuang
Ziyuan Pu
Jia Hu
Yinhai Wang
44
25
0
09 Dec 2021
Neural Network Quantization for Efficient Inference: A Survey
Neural Network Quantization for Efficient Inference: A Survey
Olivia Weng
MQ
75
26
0
08 Dec 2021
A Deep Learning Driven Algorithmic Pipeline for Autonomous Navigation in
  Row-Based Crops
A Deep Learning Driven Algorithmic Pipeline for Autonomous Navigation in Row-Based Crops
Simone Cerrato
Vittorio Mazzia
Francesco Salvetti
Mauro Martini
Simone Angarano
Alessandro Navone
Marcello Chiaberge
89
15
0
07 Dec 2021
A Generalized Zero-Shot Quantization of Deep Convolutional Neural
  Networks via Learned Weights Statistics
A Generalized Zero-Shot Quantization of Deep Convolutional Neural Networks via Learned Weights Statistics
Prasen Kumar Sharma
Arun Abraham
V. N. Rajendiran
MQ
105
8
0
06 Dec 2021
Toward Real-World Voice Disorder Classification
Toward Real-World Voice Disorder Classification
Heng-Cheng Kuo
Yu-Peng Hsieh
Huan-Hsin Tseng
Chi-Te Wang
Shih-Hau Fang
Yu Tsao
61
3
0
05 Dec 2021
Temporally Resolution Decrement: Utilizing the Shape Consistency for
  Higher Computational Efficiency
Temporally Resolution Decrement: Utilizing the Shape Consistency for Higher Computational Efficiency
Tianshu Xie
Xuan Cheng
Minghui Liu
Jiali Deng
Xiaomin Wang
Meilin Liu
SupR
42
1
0
02 Dec 2021
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via
  Generalized Straight-Through Estimation
Nonuniform-to-Uniform Quantization: Towards Accurate Quantization via Generalized Straight-Through Estimation
Zechun Liu
Kwang-Ting Cheng
Dong Huang
Eric P. Xing
Zhiqiang Shen
MQ
91
111
0
29 Nov 2021
Improved Knowledge Distillation via Adversarial Collaboration
Improved Knowledge Distillation via Adversarial Collaboration
Zhiqiang Liu
Chengkai Huang
Yanxia Liu
55
2
0
29 Nov 2021
FQ-ViT: Post-Training Quantization for Fully Quantized Vision
  Transformer
FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer
Yang Lin
Tianyu Zhang
Peiqin Sun
Zheng Li
Shuchang Zhou
ViTMQ
111
157
0
27 Nov 2021
Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator
Algorithm and Hardware Co-design for Reconfigurable CNN Accelerator
Hongxiang Fan
Martin Ferianc
Zhiqiang Que
He Li
Shuanglong Liu
Xinyu Niu
Wayne Luk
3DV
60
11
0
24 Nov 2021
Mesa: A Memory-saving Training Framework for Transformers
Mesa: A Memory-saving Training Framework for Transformers
Zizheng Pan
Peng Chen
Haoyu He
Jing Liu
Jianfei Cai
Bohan Zhuang
83
21
0
22 Nov 2021
Toward Compact Parameter Representations for Architecture-Agnostic
  Neural Network Compression
Toward Compact Parameter Representations for Architecture-Agnostic Neural Network Compression
Yuezhou Sun
Wenlong Zhao
Lijun Zhang
Xiao Liu
Hui Guan
Matei A. Zaharia
84
0
0
19 Nov 2021
E3NE: An End-to-End Framework for Accelerating Spiking Neural Networks
  with Emerging Neural Encoding on FPGAs
E3NE: An End-to-End Framework for Accelerating Spiking Neural Networks with Emerging Neural Encoding on FPGAs
Daniel Gerlinghoff
Zhehui Wang
Xiaozhe Gu
Rick Siow Mong Goh
Yaoyu Zhang
44
25
0
19 Nov 2021
Energy Efficient Learning with Low Resolution Stochastic Domain Wall
  Synapse Based Deep Neural Networks
Energy Efficient Learning with Low Resolution Stochastic Domain Wall Synapse Based Deep Neural Networks
W. A. Misba
Mark Lozano
D. Querlioz
J. Atulasimha
13
14
0
14 Nov 2021
An Underexplored Dilemma between Confidence and Calibration in Quantized
  Neural Networks
An Underexplored Dilemma between Confidence and Calibration in Quantized Neural Networks
Guoxuan Xia
Sangwon Ha
Tiago Azevedo
Partha P. Maji
UQCV
46
1
0
10 Nov 2021
AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On
  Analog Compute-in-Memory Accelerator
AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator
Chuteng Zhou
F. García-Redondo
Julian Büchel
I. Boybat
Xavier Timoneda Comas
S. Nandakumar
Shidhartha Das
Abu Sebastian
Manuel Le Gallo
P. Whatmough
78
16
0
10 Nov 2021
Ultra-Low Power Keyword Spotting at the Edge
Ultra-Low Power Keyword Spotting at the Edge
Mehmet Gorkem Ulkar
O. E. Okman
34
12
0
09 Nov 2021
ML-EXray: Visibility into ML Deployment on the Edge
ML-EXray: Visibility into ML Deployment on the Edge
Hang Qiu
Ioanna Vavelidou
Jian Li
Evgenya Pergament
Pete Warden
Sandeep P. Chinchali
Zain Asgar
Sachin Katti
49
8
0
08 Nov 2021
A Survey on Green Deep Learning
A Survey on Green Deep Learning
Jingjing Xu
Wangchunshu Zhou
Zhiyi Fu
Hao Zhou
Lei Li
VLM
203
84
0
08 Nov 2021
MQBench: Towards Reproducible and Deployable Model Quantization
  Benchmark
MQBench: Towards Reproducible and Deployable Model Quantization Benchmark
Yuhang Li
Mingzhu Shen
Jian Ma
Yan Ren
Mingxin Zhao
Qi Zhang
Ruihao Gong
F. Yu
Junjie Yan
MQ
94
51
0
05 Nov 2021
Qimera: Data-free Quantization with Synthetic Boundary Supporting
  Samples
Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples
Kanghyun Choi
Deokki Hong
Noseong Park
Youngsok Kim
Jinho Lee
MQ
71
67
0
04 Nov 2021
Weight, Block or Unit? Exploring Sparsity Tradeoffs for Speech
  Enhancement on Tiny Neural Accelerators
Weight, Block or Unit? Exploring Sparsity Tradeoffs for Speech Enhancement on Tiny Neural Accelerators
Marko Stamenovic
Nils L. Westhausen
Li-Chia Yang
Carl R. Jensen
Alex Pawlicki
68
11
0
03 Nov 2021
FAST: DNN Training Under Variable Precision Block Floating Point with
  Stochastic Rounding
FAST: DNN Training Under Variable Precision Block Floating Point with Stochastic Rounding
Shanghang Zhang
Bradley McDanel
H. T. Kung
MQ
62
69
0
28 Oct 2021
MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning
MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning
Ji Lin
Wei-Ming Chen
Han Cai
Chuang Gan
Song Han
102
161
0
28 Oct 2021
How Important is Importance Sampling for Deep Budgeted Training?
How Important is Importance Sampling for Deep Budgeted Training?
Eric Arazo
Diego Ortego
Paul Albert
Noel E. O'Connor
Kevin McGuinness
119
8
0
27 Oct 2021
NeRV: Neural Representations for Videos
NeRV: Neural Representations for Videos
Hao Chen
Bo He
Hanyu Wang
Yixuan Ren
Ser-Nam Lim
Abhinav Shrivastava
65
256
0
26 Oct 2021
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