We won the Best Paper Award of Evolutionary Machine Learning (EML) Track in GECCO 2017!
The title of the award paper is “A Genetic Programming Approach to Designing Convolutional Neural Network Architectures”. This paper achieved to find high-performance architectures of the convolutional neural networks by the genetic programming with the reasonable computational resource.
Masanori Suganuma, Shinichi Shirakawa, and Tomoharu Nagao: A Genetic Programming Approach to Designing Convolutional Neural Network Architectures, Genetic and Evolutionary Computation Conference 2017 (GECCO 2017), pp. 497-504, Berlin, Germany, 15-19 July (2017) [DOI] [arXiv] [Code]
