Viet-Anh on Software Logo

What is: Instance-Level Meta Normalization?

SourceInstance-Level Meta Normalization
Year2000
Data SourceCC BY-SA - https://paperswithcode.com

Instance-Level Meta Normalization is a normalization method that addresses a learning-to-normalize problem. ILM-Norm learns to predict the normalization parameters via both the feature feed-forward and the gradient back-propagation paths. It uses an auto-encoder to predict the weights ω\omega and bias β\beta as the rescaling parameters for recovering the distribution of the tensor xx of feature maps. Instead of using the entire feature tensor xx as the input for the auto-encoder, it uses the mean μ\mu and variance γ\gamma of xx for characterizing its statistics.