DeepSwarm: Optimising Convolutional Neural Networks using Swarm Intelligence

Edvinas Byla, Wei Pang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper we propose DeepSwarm, a novel neural architecture search (NAS) method based on Swarm Intelligence principles. At its core DeepSwarm uses Ant Colony Optimization (ACO) to generate ant population which uses the pheromone information to collectively search for the best neural architecture. Furthermore, by using local and global pheromone update rules our method ensures the balance between exploitation and exploration. On top of this, to make our method more efficient we combine progressive neural architecture search with weight reusability. Furthermore, due to the nature of ACO our method can incorporate heuristic information which can further speed up the search process. After systematic and extensive evaluation, we discover that on three different datasets (MNIST, Fashion-MNIST, and CIFAR-10) when compared to existing systems our proposed method demonstrates competitive performance. Finally, we open source DeepSwarm (https://github.com/Pattio/DeepSwarm) as a NAS library and hope it can be used by more deep learning researchers and practitioners.
Original languageEnglish
Title of host publicationAdvances in Computational Intelligence Systems
Subtitle of host publicationContributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK
EditorsZhaojie Ju, Longzhi Yang, Chenguang Yang, Alexander Gegov, Dalin Zhou
Place of PublicationCham
PublisherSpringer
Pages119-130
Number of pages12
ISBN (Electronic)9783030299330
ISBN (Print)9783030299323
DOIs
Publication statusPublished - 2020
Event19th Annual UK Workshop on Computational Intelligence - University of Portsmouth, Portsmouth, United Kingdom
Duration: 4 Sep 20196 Sep 2019

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer
Volume1043
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference19th Annual UK Workshop on Computational Intelligence
CountryUnited Kingdom
CityPortsmouth
Period4/09/196/09/19

Keywords

  • Ant Colony Optimization
  • Neural Architecture Search

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  • Prizes

    Best Paper Award for UKCI 2019

    Edvinas Byla (Recipient) & Pang, Wei (Recipient), 2019

    Prize: Awards, Distinctions, Medals, and Prizes

  • Cite this

    Byla, E., & Pang, W. (2020). DeepSwarm: Optimising Convolutional Neural Networks using Swarm Intelligence. In Z. Ju, L. Yang, C. Yang, A. Gegov, & D. Zhou (Eds.), Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK (pp. 119-130). (Advances in Intelligent Systems and Computing; Vol. 1043). Springer . https://doi.org/10.1007/978-3-030-29933-0_10