Differences
This shows you the differences between two versions of the page.
| Both sides previous revisionPrevious revisionNext revision | Previous revision | ||
| data_mining:neural_network:tuning [2018/05/20 15:10] – [Algo] phreazer | data_mining:neural_network:tuning [2018/05/20 15:21] (current) – [Batch norm at test time] phreazer | ||
|---|---|---|---|
| Line 250: | Line 250: | ||
| * Update parameters ... | * Update parameters ... | ||
| + | ==== Why does it work ==== | ||
| + | |||
| + | Covariance shift (shifting input distribution) | ||
| + | |||
| + | * Batch norm reduces amount in which hidden units shifts around, become more stable (input to later layers) | ||
| + | * Slight regularization effect: Adds some noise, because it's normed on the mini batch | ||
| + | |||
| + | ==== Batch norm at test time ==== | ||
| + | |||
| + | Here no mini-batch, but one sample at a time | ||
| + | |||
| + | Estimate $\sigma^2, \mu$ using exponentially weighted average across mini-batches | ||