Normalization Techniques in Training DNNs: Methodology, Analysis and Application-Reference-Cited by-同舟云学术

Normalization Techniques in Training DNNs: Methodology, Analysis and Application

Author:

Huang Lei¹^ORCID,Qin Jie²^ORCID,Zhou Yi³^ORCID,Zhu Fan⁴,Liu Li⁴,Shao Ling⁵^ORCID

Affiliation:

1. Institute of Artificial Intelligence of Beihang University, Beijing, China

2. Nanjing University of Aeronautics and Astronautics, Nanjing, China

3. Southeast University, Nanjing, Jiangsu, China

4. Inception Institute of Artificial Intelligence, Abu Dhabi, UAE

5. UCAS-Terminus AI Lab, University of Chinese Academy of Sciences, Beijing, China

Funder

National Key Research and Development Plan of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Link

Reference304 articles.

1. Accelerated gradient descent by factor-centering decomposition;schraudolph,1998

2. A mean field theory of batch normalization;yang;Proc Int Conf Learn Representations,2019

3. Large batch training of convolutional networks;you,2017

4. Mean-field analysis of batch normalization;wei,2019

5. Learning deep architectures via generalized whitened neural networks;luo;Proc Int Conf Mach Learn,2017

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