Genetic Network Architecture Search

Hai Victor Habi; Gil Rafalovich

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arXiv · 1907.02871

Genetic Network Architecture Search

Hai Victor Habi·Gil Rafalovich

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Abstract

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 80.1%. The code and result of this work available in GitHub:https://github.com/haihabi/GeneticNAS.

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BibTeX RIS

Hai Victor Habi, Gil Rafalovich. 2019-07-05. Genetic Network Architecture Search. https://arxiv.org/abs/1907.02871

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