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Showing 161 - 180 results of 12,685 for search '(( algorithm python function ) OR ( algorithm ((link function) OR (i function)) ))', query time: 0.53s Refine Results
  1. 161
    Definitions of global parameters used for constructing random ecosystems.

    Definitions of global parameters used for constructing random ecosystems. by Robert Marsland (8616483)

    Published 2020
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  2. 162
    WST results for LLSKSO and other algorithms on benchmark test functions. (<i>α</i> = 0.05).

    WST results for LLSKSO and other algorithms on benchmark test functions. (<i>α</i> = 0.05). by Ruyi Dong (9038174)

    Published 2025
    “…<p>WST results for LLSKSO and other algorithms on benchmark test functions. (<i>α</i> = 0.05).…”
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  3. 163
    WST results for LLSKSO and other algorithms on benchmark test functions. (<i>α</i> = 0.05).

    WST results for LLSKSO and other algorithms on benchmark test functions. (<i>α</i> = 0.05). by Ruyi Dong (9038174)

    Published 2025
    “…<p>WST results for LLSKSO and other algorithms on benchmark test functions. (<i>α</i> = 0.05).…”
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  4. 164
    Reward function related parameters.

    Reward function related parameters. by Honglei Pang (22693724)

    Published 2025
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  5. 165
    Comparison of details of different algorithms.

    Comparison of details of different algorithms. by Hao Wu (65943)

    Published 2024
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  6. 166
    Structure of the LMPEC algorithm model.

    Structure of the LMPEC algorithm model. by Hao Wu (65943)

    Published 2024
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  7. 167
    Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection

    Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection by Samin Aref (4683934)

    Published 2025
    “…Each network is provided in .gml format or .pkl format which can be read into a networkX graph object using standard functions from the networkX library in Python. For accessing other networks used in the study, please refer to the article for references to the primary sources of those network data.…”
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  8. 168
    Rosenbrock function.

    Rosenbrock function. by Rutinaldo Aguiar Nascimento (14259594)

    Published 2022
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  9. 169
    Rosenbrock function.

    Rosenbrock function. by Rutinaldo Aguiar Nascimento (14259594)

    Published 2022
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  10. 170
    Rastrigin function.

    Rastrigin function. by Rutinaldo Aguiar Nascimento (14259594)

    Published 2022
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  11. 171
    Rosenbrock function.

    Rosenbrock function. by Rutinaldo Aguiar Nascimento (14259594)

    Published 2022
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  12. 172
    Rastrigin function.

    Rastrigin function. by Rutinaldo Aguiar Nascimento (14259594)

    Published 2022
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  13. 173
    Search Algorithms and Loss Functions for Bayesian Clustering

    Search Algorithms and Loss Functions for Bayesian Clustering by David B. Dahl (11761055)

    Published 2022
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  14. 174
    Global optima for objective functions <i>f</i><sub>1</sub> –<i>f</i><sub>14</sub>.

    Global optima for objective functions <i>f</i><sub>1</sub> –<i>f</i><sub>14</sub>. by Panagiotis Aivaliotis-Apostolopoulos (13851171)

    Published 2022
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  15. 175
    Non-converging numerical solution of the non-linear equation system through the iterations <i>p</i> using the Newton-Raphson algorithm and the Levenberg–Marquardt algorithm.

    Non-converging numerical solution of the non-linear equation system through the iterations <i>p</i> using the Newton-Raphson algorithm and the Levenberg–Marquardt algorithm. by Martin Dodek (20623832)

    Published 2025
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  16. 176
    Fig 1 -

    Fig 1 - by Tian Cai (4227052)

    Published 2023
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  17. 177
    Population <i>versus</i> success rate for the Rosenbrock function.

    Population <i>versus</i> success rate for the Rosenbrock function. by Rutinaldo Aguiar Nascimento (14259594)

    Published 2022
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  18. 178
    Population <i>versus</i> success rate for the Rastrigin function.

    Population <i>versus</i> success rate for the Rastrigin function. by Rutinaldo Aguiar Nascimento (14259594)

    Published 2022
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  19. 179
    Tunable parameters in stimuli generation module. <sup><i>a</i></sup>The fixation cross is displayed once before an experiment starts to help subjects concentrate. <sup><i>b</i></sup>Different stimuli are displayed equally. If desired by the user, some stimuli can be displayed more/less frequently by assigning them a higher/lower weight.

    Tunable parameters in stimuli generation module. <sup><i>a</i></sup>The fixation cross is displayed once before an experiment starts to help subjects concentrate. <sup><i>b</i></su... by Gursimran Singh (575288)

    Published 2025
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  20. 180
    Autocorrelation functions <i>C</i>(<i>r</i>, <i>t</i>) as functions of the rescaled distance <i>r</i>/<i>R</i>(<i>t</i>) for several time points, where <i>R</i>(<i>t</i>) is determined as the position of the first zero of the raw autocorrelation function at time <i>t</i>, shown in the inset.

    Autocorrelation functions <i>C</i>(<i>r</i>, <i>t</i>) as functions of the rescaled distance <i>r</i>/<i>R</i>(<i>t</i>) for several time points, where <i>R</i>(<i>t</i>) is determ... by Marc Durand (556746)

    Published 2021
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