Art

J-GLOBAL ID：202002261042417819   Reference number：20A0507649

Efficient network architecture search via multiobjective particle swarm optimization based on decomposition

分解に基づく多目的粒子群最適化による効率的ネットワークアーキテクチャ探索

Author (8)： Jiang Jing (School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China) ,  Jiang Jing (Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace, Zhenjiang, Jiangsu, 212013, China) ,  Han Fei (School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China) ,  Han Fei (Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace, Zhenjiang, Jiangsu, 212013, China) ,  Ling Qinghua (School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212003, China) ,  Wang Jie (School of Computer Science and Technology, Anhui University, Hefei, Anhui 230039, China) ,  Li Tiange (Department of Computer and Information Sciences, Fordham University, NY 48105, USA) ,  Han Henry (Department of Computer and Information Sciences, Fordham University, NY 48105, USA)
Material： Neural Networks  (Neural Netw)
Volume： 123  Page： 305-316  Publication year： Mar. 2020 
JST Material Number： T0698A  ISSN： 0893-6080  Document type： Article
Article type： 原著論文  Country of issue： United Kingdom (GBR)  Language： ENGLISH (EN)

Thesaurus term： *neural network(biomodel) ,  search problem ,  optimization ,  trade off ,  benchmark ,  error rate ,  algorithm ,  experiment ,  classification ,  network architecture
Semi thesaurus term： optimization algorithm ,  convolutional neuralnetwork ,  multi-objective optimization ,  evaluation experiment ,  particle swarm optimization

Author keywords (4)： Convolutional neural network ,  Neural architecture search ,  Multiobjective particle swarm optimization ,  Decomposition

JST classification (1)： Artificial intelligence  (JE08000Z)

Terms in the title (4)： 分解 ,  多目的粒子群最適化 ,  ネットワークアーキテクチャ ,  探索