Cooperative execution of a genetic algorithm with an efficient training algorithm for data-driven model creation
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United States of America Patent
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Oct 10, 2017
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Apr 17, 2017
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Apr 17, 2017
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Abstract
A method includes, based on a fitness function, selecting a subset of models from a plurality of models. The plurality of models is generated based on a genetic algorithm and corresponds to a first epoch of the genetic algorithm. Each of the plurality of models includes data representative of a neural network. The method also includes performing at least one genetic operation of the genetic algorithm with respect to at least one model of the subset to generate a trainable model and sending the trainable model to an optimization trainer. The method includes adding a trained model received from the optimization trainer as input to a second epoch of the genetic algorithm that is subsequent to the first epoch.
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