Proposed algorithm. حسب Keenjhar Ayoob (22339616)

Benchmark functions. حسب Peiwen Zhang (1863202)

If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. حسب Yuanchen Zhao (12905580)

"…Both versions are evaluated on the same synthetic datasets with a 3-group ground truth. Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …"

Using synthetic data to test group-searching algorithms in a context where the correct grouping of species is known and uniquely defined. حسب Yuanchen Zhao (12905580)

Table_1_Clinical Functional Seizure Score (CFSS): a simple algorithm for clinicians to suspect functional seizures.DOCX حسب Mohammad Dashtkoohi (15417886)

One iteration of the NSGA-II algorithm. حسب Erick Axel Padilla-García (16839233)

Fitness curves of the 6 test functions. حسب Peiwen Zhang (1863202)

Simulation of multiple agents minimizing the dissonance function following homophily حسب Mohsen Raoufi (18775639)

Performance of the three algorithms. حسب Juanjuan Lin (2096830)

"…An integrated framework based on a novel genetic algorithm and the Frank—Wolfe algorithm is designed to solve the stochastic model. …"

Function <i>χ</i>_<i>opt</i> superimposed with the phase-field function indicating the channel geometry. حسب Martina Bukač (20161460)

Similarity between the hierarchical community structure of structural and functional brain graphs. حسب Arian Ashourvan (6685232)

Rosenbrock function losses for . حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. …"

Rosenbrock function losses for . حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. …"

Levy function losses for . حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. …"

Rastrigin function losses for . حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. …"

Levy function losses for . حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. …"

Rastrigin function losses for . حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. …"

Levy function losses for . حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. …"

Levy function losses for . حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. …"

Rastrigin function losses for . حسب Shikun Chen (14625352)

"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. …"