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    Multitask Sparse Bayesian Machine Learning with Applications in Modeling of Seismic Attenuation and Clay Parameters with Small Data Sets

    Source: Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 001::page 04025109-1
    Author:
    Gao, Jingze
    ,
    Wei, Shiyin
    ,
    Huang, Yong
    DOI: 10.1061/JCCEE5.CPENG-6822
    Publisher: American Society of Civil Engineers
    Abstract: AbstractMultitask sparse Bayesian learning (SBL) has received extensive attention because it makes full use of multiple groups of data by joint learning of sparse representations for multiple models. It is capable of producing superior performance, ...
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      Multitask Sparse Bayesian Machine Learning with Applications in Modeling of Seismic Attenuation and Clay Parameters with Small Data Sets

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314440
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    • Journal of Computing in Civil Engineering

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    contributor authorGao, Jingze
    contributor authorWei, Shiyin
    contributor authorHuang, Yong
    date accessioned2026-08-20T21:25:52Z
    date available2026-08-20T21:25:52Z
    date copyright2025/09/19
    date issued2026
    identifier otherJCCEE5.CPENG-6822.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314440
    description abstractAbstractMultitask sparse Bayesian learning (SBL) has received extensive attention because it makes full use of multiple groups of data by joint learning of sparse representations for multiple models. It is capable of producing superior performance, ...
    publisherAmerican Society of Civil Engineers
    titleMultitask Sparse Bayesian Machine Learning with Applications in Modeling of Seismic Attenuation and Clay Parameters with Small Data Sets
    typeJournal Article
    journal volume40
    journal issue1
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/JCCEE5.CPENG-6822
    journal fristpage04025109-1
    journal lastpage04025109-19
    page19
    treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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