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HAQ: Hardware-Aware Automated Quantization with Mixed Precision
v1v2v3 (latest)

HAQ: Hardware-Aware Automated Quantization with Mixed Precision

Computer Vision and Pattern Recognition (CVPR), 2018
21 November 2018
Kuan-Chieh Wang
Zhijian Liu
Chengyue Wu
Ji Lin
Song Han
    MQ
ArXiv (abs)PDFHTML

Papers citing "HAQ: Hardware-Aware Automated Quantization with Mixed Precision"

12 / 462 papers shown
Title
Point-Voxel CNN for Efficient 3D Deep Learning
Point-Voxel CNN for Efficient 3D Deep LearningNeural Information Processing Systems (NeurIPS), 2019
Zhijian Liu
Haotian Tang
Chengyue Wu
Song Han
3DPC
364
773
0
08 Jul 2019
Hardware/Software Co-Exploration of Neural Architectures
Hardware/Software Co-Exploration of Neural ArchitecturesIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD), 2019
Weiwen Jiang
Lei Yang
E. Sha
Qingfeng Zhuge
Shouzhen Gu
Sakyasingha Dasgupta
Yiyu Shi
Jiaxi Hu
273
138
0
06 Jul 2019
Memory-Driven Mixed Low Precision Quantization For Enabling Deep Network
  Inference On Microcontrollers
Memory-Driven Mixed Low Precision Quantization For Enabling Deep Network Inference On MicrocontrollersConference on Machine Learning and Systems (MLSys), 2019
Manuele Rusci
Alessandro Capotondi
Luca Benini
MQ
185
84
0
30 May 2019
Instant Quantization of Neural Networks using Monte Carlo Methods
Instant Quantization of Neural Networks using Monte Carlo Methods
Gonçalo Mordido
Matthijs Van Keirsbilck
A. Keller
MQ
121
9
0
29 May 2019
Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction
  in Self-Driving Cars
Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving CarsIEEE Consumer Electronics Magazine (CE), 2019
Alexandros Kouris
Stylianos I. Venieris
Michail Rizakis
C. Bouganis
AI4TS
213
12
0
02 May 2019
Low-Memory Neural Network Training: A Technical Report
Low-Memory Neural Network Training: A Technical Report
N. Sohoni
Christopher R. Aberger
Megan Leszczynski
Jian Zhang
Christopher Ré
193
110
0
24 Apr 2019
Design Automation for Efficient Deep Learning Computing
Design Automation for Efficient Deep Learning Computing
Song Han
Han Cai
Ligeng Zhu
Ji Lin
Kuan-Chieh Wang
Zhijian Liu
Chengyue Wu
131
20
0
24 Apr 2019
Resource Constrained Neural Network Architecture Search: Will a
  Submodularity Assumption Help?
Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?
Yunyang Xiong
Ronak R. Mehta
Vikas Singh
198
35
0
08 Apr 2019
AutoQ: Automated Kernel-Wise Neural Network Quantization
AutoQ: Automated Kernel-Wise Neural Network Quantization
Qian Lou
Feng Guo
Lantao Liu
Minje Kim
Lei Jiang
MQ
234
109
0
15 Feb 2019
TSM: Temporal Shift Module for Efficient Video Understanding
TSM: Temporal Shift Module for Efficient Video UnderstandingIEEE International Conference on Computer Vision (ICCV), 2018
Ji Lin
Chuang Gan
Song Han
531
1,899
0
20 Nov 2018
ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural
  Networks
ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks
Ahmed T. Elthakeb
Prannoy Pilligundla
Fatemehsadat Mireshghallah
Amir Yazdanbakhsh
H. Esmaeilzadeh
MQ
308
68
0
05 Nov 2018
A Survey of Model Compression and Acceleration for Deep Neural Networks
A Survey of Model Compression and Acceleration for Deep Neural Networks
Yu Cheng
Duo Wang
Pan Zhou
Zhang Tao
661
1,176
0
23 Oct 2017
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