A survey on evolutionary machine learning
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{Al-Sahaf:2019:JRSNZ,
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author = "Harith Al-Sahaf and Ying Bi and Qi Chen and
Andrew Lensen and Yi Mei and Yanan Sun and Binh Tran and
Bing Xue and Mengjie Zhang",
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title = "A survey on evolutionary machine learning",
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journal = "Journal of the Royal Society of New Zealand",
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year = "2019",
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volume = "49",
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number = "2",
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pages = "205--228",
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note = "The 2019 Annual Collection of Reviews",
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keywords = "genetic algorithms, genetic programming, TPOT, AI,
ANN, EML, GPU, EMO, autoML, artificial intelligence,
machine learning, evolutionary computation,
classification, regression, clustering, combinatorial
optimisation, deep learning, transfer learning,
ensemble learning",
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publisher = "Taylor \& Francis",
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URL = "https://doi.org/10.1080/03036758.2019.1609052",
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DOI = "doi:10.1080/03036758.2019.1609052",
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size = "24 pages",
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abstract = "Artificial intelligence (AI) emphasises the creation
of intelligent machines/systems that function like
humans. AI has been applied to many real-world
applications. Machine learning is a branch of AI based
on the idea that systems can learn from data, identify
hidden patterns, and make decisions with little/minimal
human intervention. Evolutionary computation is an
umbrella of population-based intelligent/learning
algorithms inspired by nature, where New Zealand has a
good international reputation. This paper provides a
review on evolutionary machine learning, i.e.
evolutionary computation techniques for major machine
learning tasks such as classification, regression and
clustering, and emerging topics including combinatorial
optimisation, computer vision, deep learning, transfer
learning, and ensemble learning. The paper also
provides a brief review of evolutionary learning
applications, such as supply chain and manufacturing
for milk/dairy, wine and seafood industries, which are
important to New Zealand. Finally, the paper presents
current issues with future perspectives in evolutionary
machine learning.",
- }
Genetic Programming entries for
Harith Al-Sahaf
Ying Bi
Qi Chen
Andrew Lensen
Yi Mei
Yanan Sun
Binh Ngan Tran
Bing Xue
Mengjie Zhang
Citations