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resource optimization » resource utilization (Expand Search), resource utilisation (Expand Search), resource limitations (Expand Search)
estimation algorithm » optimization algorithms (Expand Search), maximization algorithm (Expand Search), detection algorithm (Expand Search)
robust estimation » pose estimation (Expand Search), risk estimation (Expand Search)
task resource » a resource (Expand Search)
binary task » binary mask (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
Showing 1 - 20 results of 26 for search '(( binary task resource optimization algorithm ) OR ( binary data robust estimation algorithm ))*', query time: 0.51s Refine Results
  1. 1
    Proposed Algorithm.

    Proposed Algorithm. by Hend Bayoumi (22693738)

    Published 2025
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  2. 2
    RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values .

    RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

    Published 2023
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  3. 3
    CDF of task latency, approximated as the inverse of the achieved computation rate.

    CDF of task latency, approximated as the inverse of the achieved computation rate. by Hend Bayoumi (22693738)

    Published 2025
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  4. 4
    Comparisons between ADAM and NADAM optimizers.

    Comparisons between ADAM and NADAM optimizers. by Hend Bayoumi (22693738)

    Published 2025
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  5. 5
    Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30.

    Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30. by Hend Bayoumi (22693738)

    Published 2025
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  6. 6
    Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30.

    Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30. by Hend Bayoumi (22693738)

    Published 2025
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  7. 7
    Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification

    Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification by Vaibhavi Patel (19843282)

    Published 2024
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  8. 8
    Individual Transition Label Noise Logistic Regression in Binary Classification for Incorrectly Labeled Data

    Individual Transition Label Noise Logistic Regression in Binary Classification for Incorrectly Labeled Data by Seokho Lee (10088)

    Published 2021
    “…<p>We consider a binary classification problem in the case where some observations in the training data are incorrectly labeled. …”
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  9. 9
    An Example of a WPT-MEC Network.

    An Example of a WPT-MEC Network. by Hend Bayoumi (22693738)

    Published 2025
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  10. 10
    Related Work Summary.

    Related Work Summary. by Hend Bayoumi (22693738)

    Published 2025
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  11. 11
    Simulation parameters.

    Simulation parameters. by Hend Bayoumi (22693738)

    Published 2025
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  12. 12
    Training losses for N = 10.

    Training losses for N = 10. by Hend Bayoumi (22693738)

    Published 2025
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  13. 13
    Performance Comparison of State-of-the-Art WPT-MEC Offloading Methods.

    Performance Comparison of State-of-the-Art WPT-MEC Offloading Methods. by Hend Bayoumi (22693738)

    Published 2025
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  14. 14
    The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames.

    The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames. by Hend Bayoumi (22693738)

    Published 2025
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  15. 15
    Normalized computation rate for N = 10.

    Normalized computation rate for N = 10. by Hend Bayoumi (22693738)

    Published 2025
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  16. 16
    Comparison between Bisection and Newton-Raphson in terms of (A) total time consumed, and (B) maximum computation rate.

    Comparison between Bisection and Newton-Raphson in terms of (A) total time consumed, and (B) maximum computation rate. by Hend Bayoumi (22693738)

    Published 2025
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  17. 17
    Summary of Notations Used in this paper.

    Summary of Notations Used in this paper. by Hend Bayoumi (22693738)

    Published 2025
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  18. 18
    Reverse engineering information flow using stimulus-encoding and stimulus-transfer estimation algorithms.

    Reverse engineering information flow using stimulus-encoding and stimulus-transfer estimation algorithms. by Gabriel Matías Lorenz (21094672)

    Published 2025
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  19. 19
    Determination of the Solute Content and Volumetric Properties of Binary Ionic Liquid Mixtures Using a Global Regularity of Molar Volume Expansion

    Determination of the Solute Content and Volumetric Properties of Binary Ionic Liquid Mixtures Using a Global Regularity of Molar Volume Expansion by Javad Hekayati (1383249)

    Published 2021
    “…For instance, the water content, which is of great significance in IL studies, can easily be estimated using the proposed algorithm. By doing so, an overall AARD of 3.47% was obtained for the estimation of the water content of 68 binary systems. …”
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  20. 20
    Fig 1 -

    Fig 1 - by Jakub Stoklosa (3315042)

    Published 2023
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