Genetic Network Architecture Search

07/05/2019

∙

by   Hai Victor Habi, et al.

∙

Tel Aviv University

∙

12

∙

share

We propose a method for learning the neural network architecture that based on Genetic Algorithm (GA). Our approach uses a genetic algorithm integrated with standard Stochastic Gradient Descent(SGD) which allows the sharing of weights across all architecture solutions. The method uses GA to design a sub-graph of Convolution cell which maximizes the accuracy on the validation-set. Through experiments, we demonstrate this methods performance on both CIFAR10 and CIFAR100 dataset with an accuracy of 96 and result of this work available in GitHub:https://github.com/haihabi/GeneticNAS.