Recombination of Artificial Neural Networks

12 Jan 2019Aaron VoseJacob BalmaAlex HeyeAlessandro RigazziCharles SiegelDiana MoiseBenjamin RobbinsRangan Sukumar

We propose a genetic algorithm (GA) for hyperparameter optimization of artificial neural networks which includes chromosomal crossover as well as a decoupling of parameters (i.e., weights and biases) from hyperparameters (e.g., learning rate, weight decay, and dropout) during sexual reproduction. Children are produced from three parents; two contributing hyperparameters and one contributing the parameters... (read more)

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