Showing 1 - 20 results of 43 for search '(((( algorithm b function ) OR ( algorithms loss function ))) OR ( algorithm python function ))', query time: 0.13s Refine Results
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    Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

    Published 2022
    “…The performance of three machine learning (ML) algorithms was assessed to predict the wild blueberry harvest losses on the ground. …”
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    A New Penalty Function Algorithm For Convex Quadratic Programming by Bendaya, M.

    Published 2020
    “…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
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    Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures by Iryna Haponchyk (19691701)

    Published 2017
    “…In this paper, we trade off exact computation for enabling the use and study of more complex loss functions for coreference resolution. Most interestingly, we show that such functions can be (i) automatically learned also from controversial but commonly accepted coreference measures, e.g., MELA, and (ii) successfully used in learning algorithms. …”
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    Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm by Noor Habib Khan (22224775)

    Published 2024
    “…To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. For validation of ILCA, the non‐parametric and the statistical analysis are performed using benchmark standard functions. …”
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    A new reactive power optimization algorithm by Mantawy, A.H.

    Published 2003
    “…A new implementation for the particle swarm algorithm has been applied. The objective function of the proposed algorithm is to minimize the system active power loss. …”
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    Cohen syndrome and early-onset epileptic encephalopathy in male triplets: two disease-causing mutations in VPS13B and NAPB by Alice AbdelAleem (17753799)

    Published 2023
    “…Interestingly, the functions of the two proteins; VPS13B, a transmembrane protein involved in intracellular protein transport, and SNAP-beta involved in neurotransmitters release at the neuronal synaptic complexes, have been associated with Golgi-mediated vesicular trafficking. …”
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    Android Malware Detection Using Machine Learning by Al Ali, Shaikha

    Published 2024
    “…Detecting and preventing malware is crucial for several reasons, including the security of personal information, data loss and tampering, system disruptions, financial losses, and reputation damage. …”
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    A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

    Published 2023
    “…The proposed model determines a training dataset by covering all the aspects of cost function calculation. This training dataset helps to train the model, which allows for efficient decision-making in optimum energy usage. …”
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    A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance by Krishnamoorthy Natarajan (22047464)

    Published 2024
    “…Hence, in this study, deep learning algorithms, such as VGG16, EfficientNetB4, and ResNet, are utilized to diagnose various diseases, such as Alzheimer's, brain tumors, skin diseases, and lung diseases. …”
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    Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation by Raveendra Pilli (21633287)

    Published 2024
    “…Moreover, the proposed algorithm demonstrated excellent prediction accuracy with a mean absolute error (MAE) of <b>3.89</b> years, <b>3.64 </b>years, and <b>4.49</b> years for GM, WM, and CSF regions, confirming that changes in WM volume are significantly associated with normal brain aging. …”