Optimization-Based Post-Training Quantization With Bit-Split and Stitching

Author:

Wang Peisong1ORCID,Chen Weihan1,He Xiangyu1,Chen Qiang1ORCID,Liu Qingshan2ORCID,Cheng Jian1ORCID

Affiliation:

1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China

2. B-DAT, Nanjing University of Information Science and Technology, Nanjing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Strategic Priority Research Program of Chinese Academy of Sciences

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Reference76 articles.

1. Accelerating Convolutional Neural Networks for Mobile Applications

2. Collaborative channel pruning for deep networks;peng;Proc Int Conf Mach Learn,2019

3. Quantized Convolutional Neural Networks for Mobile Devices

4. Quantizing deep convolutional networks for efficient inference: A whitepaper;krishnamoorthi,2018

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