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Genetic programming for cross-task knowledge sharing

Published: 07 July 2007 Publication History

Abstract

We consider multitask learning of visual concepts within genetic programming (GP) framework. The proposed method evolves a population of GP individuals, with each of them composed of several GP trees that process visual primitives derived from input images. The two main trees are delegated to solving two different visual tasks and are allowed to share knowledge with each other by calling the remaining GP trees (subfunctions) included in the same individual. The method is applied to the visual learning task of recognizing simple shapes, using generative approach based on visual primitives. We compare this approach to a reference method devoid of knowledge sharing, and conclude that in the worst case cross-task learning performs equally well, and in many cases it leads to significant performance improvements in one or both solved tasks.

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    cover image ACM Conferences
    GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
    July 2007
    2313 pages
    ISBN:9781595936974
    DOI:10.1145/1276958
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 07 July 2007

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    Author Tags

    1. genetic programming
    2. knowledge sharing
    3. multitask learning
    4. representations

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    GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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    • (2018)Locally geometric semantic crossoverGenetic Programming and Evolvable Machines10.1007/s10710-012-9172-714:1(31-63)Online publication date: 24-Dec-2018
    • (2010)Automatic generation and exploitation of related problems in genetic programmingIEEE Congress on Evolutionary Computation10.1109/CEC.2010.5586120(1-8)Online publication date: Jul-2010
    • (2010)Coevolutionary Temporal Difference Learning for small-board GoIEEE Congress on Evolutionary Computation10.1109/CEC.2010.5586054(1-8)Online publication date: Jul-2010
    • (2007)Knowledge reuse in genetic programming applied to visual learningProceedings of the 9th annual conference on Genetic and evolutionary computation10.1145/1276958.1277318(1790-1797)Online publication date: 7-Jul-2007
    • (2007)Learning and Recognition of Hand-Drawn Shapes Using Generative Genetic ProgrammingApplications of Evolutinary Computing10.1007/978-3-540-71805-5_31(281-290)Online publication date: 2007

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