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Weight standardization is a normalization technique used in conjunction with group normalization for training neural networks, as discussed by C1 Cow, Shan Chi Yu, Wei Shen, and Alan Yu at John Hopkins University. This technique is commonly used in combination with group normalization to improve performance. Results show that weight standardization used with group normalization can outperform batch normalization and group normalization alone in ImageNet top one accuracy. This paper emphasizes the importance of using weight standardization with group normalization for better results in training neural networks.
