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Showing 1 - 14 results of 14 for search '(( binary _ joint optimization algorithm ) OR ( primary data whale optimization algorithm ))', query time: 0.45s Refine Results
  1. 1
    Total primary energy demand by fuel in China.

    Total primary energy demand by fuel in China. by Da Lian (18880882)

    Published 2024
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  2. 2
    Homomorphic binary tree.

    Homomorphic binary tree. by Jianhua He (341366)

    Published 2024
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  3. 3
    Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations.

    Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. by Tristan Mary-Huard (3864)

    Published 2023
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  4. 4
    Proposed model tuned hyperparameters.

    Proposed model tuned hyperparameters. by Subathra Gunasekaran (19492680)

    Published 2024
    “…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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  5. 5
    The workflow of the proposed model.

    The workflow of the proposed model. by Subathra Gunasekaran (19492680)

    Published 2024
    “…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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  6. 6
    ResNeXt101 training and results.

    ResNeXt101 training and results. by Subathra Gunasekaran (19492680)

    Published 2024
    “…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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  7. 7
    Proposed model specificity and DSC outcomes.

    Proposed model specificity and DSC outcomes. by Subathra Gunasekaran (19492680)

    Published 2024
    “…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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  8. 8
    Accuracy comparison of proposed and other models.

    Accuracy comparison of proposed and other models. by Subathra Gunasekaran (19492680)

    Published 2024
    “…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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  9. 9
    Architecture of ConvNet.

    Architecture of ConvNet. by Subathra Gunasekaran (19492680)

    Published 2024
    “…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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  10. 10
    Comparison of state-of-the-art method.

    Comparison of state-of-the-art method. by Subathra Gunasekaran (19492680)

    Published 2024
    “…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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  11. 11
    Proposed model sensitivity outcome.

    Proposed model sensitivity outcome. by Subathra Gunasekaran (19492680)

    Published 2024
    “…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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  12. 12
    Proposed ResNeXt101 operational flow.

    Proposed ResNeXt101 operational flow. by Subathra Gunasekaran (19492680)

    Published 2024
    “…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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  13. 13
    Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes

    Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes by Yu Y. (3096192)

    Published 2022
    “…We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …”
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  14. 14
    Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods

    Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods by Jiacong Du (12035845)

    Published 2022
    “…Building on existing work, we (i) derive and implement efficient cyclic coordinate descent and majorization-minimization optimization algorithms for continuous and binary outcome data, (ii) incorporate adaptive shrinkage penalties, (iii) compare these methods through simulation, and (iv) develop an R package <i>miselect</i>. …”
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