Importance

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Abstract

A method and apparatus are provided that reduce the training time associated with machine learning systems whose training time is proportional to the number of outputs being trained. Under embodiments of the invention, the number of outputs to be trained is reduced by dividing the objects to be modeled into classes. This produces at least two sets of model parameters. At least one set describes some aspect of the classes given some context, and at least one other set of parameters describes some aspect of the objects given a class and the context. Thus, instead of training a system with a large number of outputs, corresponding to all of the objects, the present invention trains at least two models, each of which has a much smaller number of outputs.

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First Claim