Image Feature Learning with a Genetic Programming Autoencoder
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Ruberto:2020:GECCOcompa,
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author = "Stefano Ruberto and Valerio Terragni and
Jason H. Moore",
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title = "Image Feature Learning with a Genetic Programming
Autoencoder",
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year = "2020",
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editor = "Richard Allmendinger and Hugo Terashima Marin and
Efren Mezura Montes and Thomas Bartz-Beielstein and
Bogdan Filipic and Ke Tang and David Howard and
Emma Hart and Gusz Eiben and Tome Eftimov and
William {La Cava} and Boris Naujoks and Pietro Oliveto and
Vanessa Volz and Thomas Weise and Bilel Derbel and Ke Li and
Xiaodong Li and Saul Zapotecas and Qingfu Zhang and
Rui Wang and Ran Cheng and Guohua Wu and Miqing Li and
Hisao Ishibuchi and Jonathan Fieldsend and
Ozgur Akman and Khulood Alyahya and Juergen Branke and
John R. Woodward and Daniel R. Tauritz and Marco Baioletti and
Josu Ceberio Uribe and John McCall and
Alfredo Milani and Stefan Wagner and Michael Affenzeller and
Bradley Alexander and Alexander (Sandy) Brownlee and
Saemundur O. Haraldsson and Markus Wagner and
Nayat Sanchez-Pi and Luis Marti and Silvino {Fernandez Alzueta} and
Pablo {Valledor Pellicer} and Thomas Stuetzle and
Matthew Johns and Nick Ross and Ed Keedwell and
Herman Mahmoud and David Walker and Anthony Stein and
Masaya Nakata and David Paetzel and Neil Vaughan and
Stephen Smith and Stefano Cagnoni and Robert M. Patton and
Ivanoe {De Falco} and Antonio {Della Cioppa} and
Umberto Scafuri and Ernesto Tarantino and
Akira Oyama and Koji Shimoyama and Hemant Kumar Singh and
Kazuhisa Chiba and Pramudita Satria Palar and Alma Rahat and
Richard Everson and Handing Wang and Yaochu Jin and
Erik Hemberg and Riyad Alshammari and
Tokunbo Makanju and Fuijimino-shi and Ivan Zelinka and Swagatam Das and
Ponnuthurai Nagaratnam and Roman Senkerik",
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publisher = "Association for Computing Machinery",
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publisher_address = "New York, NY, USA",
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booktitle = "Proceedings of the 2020 Genetic and Evolutionary
Computation Conference Companion",
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pages = "245--246",
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address = "internet",
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series = "GECCO '20",
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month = jul # " 8-12",
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organisation = "SIGEVO",
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keywords = "genetic algorithms, genetic programming, feature
learning, autoencoder, MNIST",
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isbn13 = "9781450371278",
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URL = "https://valerio65.github.io/assets/pdf/ruberto-gecco-2020.pdf",
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URL = "https://doi.org/10.1145/3377929.3389981",
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DOI = "doi:10.1145/3377929.3389981",
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size = "2 pages",
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abstract = "Learning features from raw data is an important topic
in machine learning. This paper presents a novel GP
approach to learn high-level features from 2D images.
It is a generative approach that resembles the concept
of an autoencoder. Our approach executes multiple GP
runs, each run generates a (partial) model that focuses
on a particular high-level feature of the training
images. Then, it combines the models generated by each
run into a parametric function that reconstructs the
observed images. We evaluated our approach on the
popular MNIST dataset of 2D images representing
handwritten digits. Our evaluation results show that
our parametric approach can precisely reconstruct the
MNIST hand-written digits.",
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notes = "Also known as \cite{ruberto-gecco-2020} Also known as
\cite{10.1145/3377929.3389981} GECCO-2020 A
Recombination of the 29th International Conference on
Genetic Algorithms (ICGA) and the 25th Annual Genetic
Programming Conference (GP)",
- }
Genetic Programming entries for
Stefano Ruberto
Valerio Terragni
Jason H Moore
Citations