@inproceedings{e647d4709a2b4636802468ad331694ff,
title = "Evolving neural architecture using one shot model",
abstract = "Previous evolution based architecture search require high computational resources resulting in large search time. In this work, we propose a novel way of applying a simple genetic algorithm to the neural architecture search problem called EvNAS (Evolving Neural Architecture using One Shot Model) which reduces the search time significantly while still achieving better result than previous evolution based methods. The architectures are represented by architecture parameter of one shot model which results in the weight sharing among the given population of architectures and also weight inheritance from one generation to the next generation of architectures. We use the accuracy of partially trained architecture on validation data as a prediction of its fitness to reduce the search time. We also propose a decoding technique for the architecture parameter which is used to divert majority of the gradient information towards the given architecture and is also used for improving the fitness prediction of the given architecture from the one shot model during the search process. EvNAS searches for architecture on CIFAR-10 for 3.83 GPU day on a single GPU with top-1 test error 2.47%, which is then transferred to CIFAR-100 and ImageNet achieving top-1 error 16.37% and top-5 error 7.4% respectively.",
keywords = "Decoded architecture parameter, Genetic algorithm, One shot model",
author = "Nilotpal Sinha and Chen, {Kuan Wen}",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 2021 Genetic and Evolutionary Computation Conference, GECCO 2021 ; Conference date: 10-07-2021 Through 14-07-2021",
year = "2021",
month = jun,
day = "26",
doi = "10.1145/3449639.3459275",
language = "English",
series = "GECCO 2021 - Proceedings of the 2021 Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery, Inc",
pages = "910--918",
booktitle = "GECCO 2021 - Proceedings of the 2021 Genetic and Evolutionary Computation Conference",
}