Showing 141 - 160 results of 492 for search '(( algorithm where function ) OR ( ((algorithm python) OR (algorithm flow)) function ))*', query time: 0.50s Refine Results
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    State Function-Based Correction: A Simple and Efficient Free-Energy Correction Algorithm for Large-Scale Relative Binding Free-Energy Calculations by Runduo Liu (10756379)

    Published 2025
    “…We present an efficient and straightforward State Function-based Correction (SFC) algorithm, which leverages the state function property of free energy without requiring cycle identification. …”
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    Ms.FPOP: A Fast Exact Segmentation Algorithm with a Multiscale Penalty by Arnaud Liehrmann (10970682)

    Published 2024
    “…This penalty was proposed by Verzelen et al. and achieves optimal rates for changepoint detection and changepoint localization in a non-asymptotic scenario. Our proposed algorithm, Multiscale Functional Pruning Optimal Partitioning (Ms.FPOP), extends functional pruning ideas presented in Rigaill and Maidstone et al. to multiscale penalties. …”
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    Optimization outcome for the Rosenbrock function. by Shikun Chen (14625352)

    Published 2025
    “…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…”
  8. 148

    Optimization outcome for the Rastrigin function. by Shikun Chen (14625352)

    Published 2025
    “…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…”
  9. 149

    2D Rastrigin function. by Shikun Chen (14625352)

    Published 2025
    “…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…”
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    2D Levy function. by Shikun Chen (14625352)

    Published 2025
    “…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…”
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    2D Rosenbrock function. by Shikun Chen (14625352)

    Published 2025
    “…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…”
  12. 152

    Optimization outcome for the Levy function. by Shikun Chen (14625352)

    Published 2025
    “…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…”
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