Keywords

#neural_scaling_law

Neural scaling law

Law in machine learning

In machine learning, a neural scaling law is an empirical scaling law that describes how neural network performance changes as key factors are scaled up or down. These factors typically include the number of parameters, training dataset size, and training cost.

Wed 18th

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