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Showing 1 - 20 results of 399 for search '(((( complement based algorithm ) OR ( element lasso algorithm ))) OR ( level coding algorithm ))', query time: 0.42s Refine Results
  1. 1
    Numbers of iterations (#Ite) and eigenvalue calculations (#Eig) in the DC algorithm on the random and chain graph datasets.

    Numbers of iterations (#Ite) and eigenvalue calculations (#Eig) in the DC algorithm on the random and chain graph datasets. by Tomokaze Shiratori (9635271)

    Published 2024
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  2. 2
    Main code.

    Main code. by Jingguo Bi (21439766)

    Published 2025
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  3. 3
    Phenotype frequencies for each mutant and for complementation testing.

    Phenotype frequencies for each mutant and for complementation testing. by McKenna Feltes (11242085)

    Published 2025
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  4. 4
    Phenotype frequency and complementation for additional novel DY alleles.

    Phenotype frequency and complementation for additional novel DY alleles. by McKenna Feltes (11242085)

    Published 2025
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  5. 5
    Pseudo-code of large neighborhood search (<i>LNS</i>) algorithm.

    Pseudo-code of large neighborhood search (<i>LNS</i>) algorithm. by Jiren CAO (20442214)

    Published 2024
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  6. 6
    Chromosome coding.

    Chromosome coding. by Junjie He (700642)

    Published 2024
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  7. 7
    Open-source code for the Spatial Optimization Model for Land Use (SSFLA-MLAS)

    Open-source code for the Spatial Optimization Model for Land Use (SSFLA-MLAS) by bowen pang (21837359)

    Published 2025
    “…<p dir="ltr">The open-source content is the source code of a land use spatial optimization model (SSFLA-MLAS) that couples the spatial leapfrog algorithm with multi-level multi-agent systems. …”
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  8. 8
    The ranking of algorithms with MPTM mutation by TOPSIS.

    The ranking of algorithms with MPTM mutation by TOPSIS. by Jalal- ud-Din (21474307)

    Published 2025
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  9. 9
    The ranking of algorithms with NUM mutation by TOPSIS.

    The ranking of algorithms with NUM mutation by TOPSIS. by Jalal- ud-Din (21474307)

    Published 2025
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  10. 10
    The ranking of algorithms with PM mutation by TOPSIS.

    The ranking of algorithms with PM mutation by TOPSIS. by Jalal- ud-Din (21474307)

    Published 2025
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  11. 11
    Computation time as a function of the sample size on the chain graph dataset.

    Computation time as a function of the sample size on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  12. 12
    Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges).

    Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

    Published 2024
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  13. 13
    Computation time as a function of the sample size on the random graph dataset.

    Computation time as a function of the sample size on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  14. 14
    F1 score of edges selected through cross-validation on the chain graph dataset.

    F1 score of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  15. 15
    Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges).

    Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

    Published 2024
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  16. 16
    Examples of ground-truth graph structures with (<i>p</i>, <i>n</i><sub>≠0</sub>) = (10, 10).

    Examples of ground-truth graph structures with (<i>p</i>, <i>n</i><sub>≠0</sub>) = (10, 10). by Tomokaze Shiratori (9635271)

    Published 2024
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  17. 17
    Number of edges selected through cross-validation on the chain graph dataset.

    Number of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  18. 18
    Number of edges selected through cross-validation on the random graph dataset.

    Number of edges selected through cross-validation on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  19. 19
    Graphs of the regularization terms.

    Graphs of the regularization terms. by Tomokaze Shiratori (9635271)

    Published 2024
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  20. 20
    F1 score of a given number of selected edges on the chain graph dataset.

    F1 score of a given number of selected edges on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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