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by yobbo 507 days ago
For example, if it is meaningful to use large batch sizes, the gradient variance will be lower and adam could be equivalent to just momentum.

As a model is trained, the gradient variance typically falls.

Those optimizers all work to reduce the variance of the updates in various ways.