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Showing 1 - 20 results of 57 for search '(( binary b process optimization algorithm ) OR ( binary _ robust estimation algorithm ))', query time: 0.59s Refine Results
  1. 1
    a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset.

    a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset. by Nebojsa Bacanin (13932723)

    Published 2022
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  2. 2
    Fig 1 -

    Fig 1 - by Jakub Stoklosa (3315042)

    Published 2023
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  3. 3
    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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  4. 4
    Generalized Low-Rank Plus Sparse Tensor Estimation by Fast Riemannian Optimization

    Generalized Low-Rank Plus Sparse Tensor Estimation by Fast Riemannian Optimization by Jian-Feng Cai (498405)

    Published 2022
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  5. 5
    Proposed Algorithm.

    Proposed Algorithm. by Hend Bayoumi (22693738)

    Published 2025
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  6. 6
    <i>hi</i>PRS algorithm process flow.

    <i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

    Published 2023
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  7. 7
    Comparisons between ADAM and NADAM optimizers.

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

    Published 2025
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  8. 8
    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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  9. 9
    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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  10. 10
    Optimization of tracking parameters based on <i>P</i><sub><i>swap</i></sub>.

    Optimization of tracking parameters based on <i>P</i><sub><i>swap</i></sub>. by Benjamin Gallois (10131683)

    Published 2021
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  11. 11
    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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  12. 12
    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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  13. 13
    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
    “…We propose an efficient algorithm under the thresholding rule for individual parameter estimation. …”
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  14. 14
    The data processing and analysis pipeline.

    The data processing and analysis pipeline. by Xin Zhang (35492)

    Published 2025
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  15. 15
    The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus requiring fewer qubits.

    The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus re... by Aninda Astuti (21736334)

    Published 2025
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  16. 16
    Fig 4 -

    Fig 4 - by Olaide N. Oyelade (14047002)

    Published 2023
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  17. 17
    Fig 7 -

    Fig 7 - by Olaide N. Oyelade (14047002)

    Published 2023
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  18. 18
    Fig 2 -

    Fig 2 - by Olaide N. Oyelade (14047002)

    Published 2023
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  19. 19
    An illustration and comparison of the fitness convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using 50 and 100 population sizes.

    An illustration and comparison of the fitness convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using... by Olaide N. Oyelade (14047002)

    Published 2023
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  20. 20
    An illustration and comparison of the cost convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using 50 and 100 population sizes.

    An illustration and comparison of the cost convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using 50... by Olaide N. Oyelade (14047002)

    Published 2023
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