Batch Normalization in Deep Learning
Learn about batch normalization, a technique that speeds up training of deep networks by subtracting the mean and dividing by variance, improving accuracy. Explore the concept, how it works, and its effectiveness compared to group normalization.
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Presentation Transcript
Batch normalization in deep learning Usman Roshan
What is batch normalization? Subtract mean and divide by variance Alternatively set input Euclidean length to 1 Speeds up training of deep networks Improves accuracy From Ioffe and Szegedy https://arxiv.org/abs/1502.0316 7
Batch normalization From Ioffe and Szegedy https://arxiv.org/abs/1502.0316 7
Batch normalization Why does it work? Conjecture: reduces internal covariate shift (ICS) ICS is the change in distribution of layer inputs caused by updates to previous layers Recent study challenges this conjecture with empirical results
Group normalization Four types of normalization: From Ioffe and Szegedy https://arxiv.org/abs/1502.0316 7
