staged training

A tactic of training a model in a sequence of discrete stages. The goal can be either to speed up the training process, or to achieve better model quality. An illustration of the progressive stacking approach is shown below: - Stage 1 contains 3 hidden layers, stage 2 contains 6 hidden layers, and stage 3 contains 12 hidden layers. - Stage 2 begins training with the weights learned in the 3 hidden layers of Stage 1. Stage 3 begins training with the weights learned in the 6 hidden layers of Stage 2. See also pipelining.

Practitioners refer to staged training when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.