Seonglae ChoAcross the batch dimension, any neuron to have unit gaussian distribution
레이어마다 Normalization을 하는 레이어를 두어, 변형된 분포가 나오지 않도록 하는 것
Layer Normalization 에서 차원 하나만 바꾸면 된다
Limitation
- dependent to mini batch size
- hard to apply to RNN
Batch Normalization Methods
배치 정규화(Batch Normalization)
gaussian37's blog
https://gaussian37.github.io/dl-concept-batchnorm/
Batch normalization
Batch normalization is a method used to make training of artificial neural networks faster and more stable through normalization of the layers' inputs by re-centering and re-scaling. It was proposed by Sergey Ioffe and Christian Szegedy in 2015.
https://en.wikipedia.org/wiki/Batch_normalization
Google Patent
Batch normalization layers
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing inputs using a neural network system that includes a batch normalization layer. One of the methods includes receiving a respective first layer output for each training example in the batch; computing a plurality of normalization statistics for the batch from the first layer outputs; normalizing each component of each first layer output using the normalization statistics to generate a respective normalized layer output for each training example in the batch; generating a respective batch normalization layer output for each of the training examples from the normalized layer outputs; and providing the batch normalization layer output as an input to the second neural network layer.
https://patents.google.com/patent/US20160217368A1/en