Multitask Visual Learning Using Genetic Programming

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@Article{Jaskowski:2008:EC,

• author = "Wojciech Jaskowski and Krzysztof Krawiec and Bartosz Wieloch",
• title = "Multitask Visual Learning Using Genetic Programming",
• journal = "Evolutionary Computation",
• year = "2008",
• volume = "16",
• number = "4",
• pages = "439--459",
• month = "Winter",
• keywords = "genetic algorithms, genetic programming",
• ISSN = "1063-6560",
• DOI = "doi:10.1162/evco.2008.16.4.439",
• abstract = "We propose a multi-task learning method of visual concepts within the genetic programming (GP) framework. Each GP individual is composed of several trees that process visual primitives derived from input images. Two trees solve two different visual tasks and are allowed to share knowledge with each other by commonly calling the remaining GP trees (sub functions) included in the same individual. The performance of a particular tree is measured by its ability to reproduce the shapes contained in the training images. We apply this method to visual learning tasks of recognizing simple shapes and compare it to a reference method. The experimental verification demonstrates that such multitask learning often leads to performance improvements in one or both solved tasks, without extra computational effort.",
• notes = "Part of special issue on Evolutionary Computer Vision \cite{Cagnoni:2008:EC}",

}

Genetic Programming entries for Wojciech Jaskowski Krzysztof Krawiec Bartosz Wieloch

Citations