يعرض 81 - 100 نتائج من 15,808 نتيجة بحث عن '(((( algorithm a function ) OR ( algorithm l function ))) OR ( algorithm python function ))*', وقت الاستعلام: 0.39s تنقيح النتائج
  1. 81

    Non-Iterative Linear Maximization Algorithm حسب Gerardo L. Febres (4455913)

    منشور في 2019
    "…</div><div><br></div><div>Search "A non-iterative method for optimizing linear functions in convex linearly constrained spaces" by Gerardo L. …"
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    The Effect of Machine Learning Algorithms on the Prediction of Layer-by-Layer Coating Properties حسب Tijana Šušteršič (14519970)

    منشور في 2023
    "…However, despite the number of publications related to LbL assembly, predicting LbL coating properties represents quite a challenge, can take a long time, and be very costly. …"
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    Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement حسب Antoine Falisse (6061601)

    منشور في 2019
    "…<div><p>Algorithmic differentiation (AD) is an alternative to finite differences (FD) for evaluating function derivatives. …"
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  13. 93

    FRACTIONAL ORDER LOG BARRIER INTERIOR POINT ALGORITHM FOR POLYNOMIAL REGRESSION IN THE ℓ p -NORM حسب Eliana Contharteze Grigoletto (14178517)

    منشور في 2022
    "…<div><p>ABSTRACT Fractional calculus is the branch of mathematics that studies the several possibilities of generalizing the derivative and integral of a function to noninteger order. Recent studies found in literature have confirmed the importance of fractional calculus for minimization problems. …"
  14. 94

    Simulation results for average reward rate function using the UCB algorithm , where <i>A</i> = 100, <i></i> = 20, <i>μ</i> = [0.75, …(×50), 0.5, …(×50)], and <i>T</i> = 1000, and . حسب Justin Zobel (241587)

    منشور في 2022
    "…<p>Simulation results for average reward rate function using the UCB algorithm , where <i>A</i> = 100, <i></i> = 20, <i>μ</i> = [0.75, …(×50), 0.5, …(×50)], and <i>T</i> = 1000, and .…"
  15. 95

    Development and Evaluation of GlycanDock: A Protein–Glycoligand Docking Refinement Algorithm in Rosetta حسب Morgan L. Nance (10981871)

    منشور في 2021
    "…These highly diverse chains are recognized by a variety of protein receptors, enabling glycans to regulate many biological functions. …"
  16. 96

    Development and Evaluation of GlycanDock: A Protein–Glycoligand Docking Refinement Algorithm in Rosetta حسب Morgan L. Nance (10981871)

    منشور في 2021
    "…These highly diverse chains are recognized by a variety of protein receptors, enabling glycans to regulate many biological functions. …"
  17. 97

    Development and Evaluation of GlycanDock: A Protein–Glycoligand Docking Refinement Algorithm in Rosetta حسب Morgan L. Nance (10981871)

    منشور في 2021
    "…These highly diverse chains are recognized by a variety of protein receptors, enabling glycans to regulate many biological functions. …"
  18. 98

    Development and Evaluation of GlycanDock: A Protein–Glycoligand Docking Refinement Algorithm in Rosetta حسب Morgan L. Nance (10981871)

    منشور في 2021
    "…These highly diverse chains are recognized by a variety of protein receptors, enabling glycans to regulate many biological functions. …"
  19. 99

    Development and Evaluation of GlycanDock: A Protein–Glycoligand Docking Refinement Algorithm in Rosetta حسب Morgan L. Nance (10981871)

    منشور في 2021
    "…These highly diverse chains are recognized by a variety of protein receptors, enabling glycans to regulate many biological functions. …"
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