- author = "James McDermott",
- title = "Why is Auto-Encoding Difficult for Genetic Programming?",
- booktitle = "EuroGP 2019: Proceedings of the 22nd European Conference on Genetic Programming",
- year = "2019",
- month = "24-26 " # apr,
- editor = "Lukas Sekanina and Ting Hu and Nuno Lourenco",
- series = "LNCS",
- volume = "11451",
- publisher = "Springer Verlag",
- address = "Leipzig, Germany",
- pages = "131--145",
- organisation = "EvoStar, Species",
- keywords = "genetic algorithms, genetic programming",
- isbn13 = "978-3-030-16669-4",
-
URL = "
https://www.springer.com/us/book/9783030166694",
-
DOI = "
doi:10.1007/978-3-030-16670-0_9",
- size = "16 pages",
- abstract = "Unsupervised learning is an important component in many recent successes in machine learning. The autoencoder neural network is one of the most prominent approaches to unsupervised learning. Here, we use the genetic programming paradigm to create autoencoders and find that the task is difficult for genetic programming, even on small datasets which are easy for neural networks. We investigate which aspects of the autoencoding task are difficult for genetic programming.",
-
notes = "EuroGP Best Paper
Candidate
http://www.evostar.org/2019/cfp_eurogp.php#abstracts Part of \cite{Sekanina:2019:GP} EuroGP'2019 held in conjunction with EvoCOP2019, EvoMusArt2019 and EvoApplications2019",
