Levy function losses for . by Shikun Chen (14625352)

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Rastrigin function losses for . by Shikun Chen (14625352)

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Rastrigin function losses for . by Shikun Chen (14625352)

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Rosenbrock function losses for . by Shikun Chen (14625352)

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Flow chart diagram of quantum hash function. by Sultan H. Almotiri (14029251)

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IDRAS algorithm outline. by Ron Teichner (21492434)

A comparative workflow of all six functional software tools producing GO term lists from the same dataset. by Ray Sajulga (5721518)

Comparison of the smooth-index (‘SI’) algorithm with feedback arc set (‘FAS’) sorting. by Alexander Borst (32619)

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Application of the smooth-index algorithm to the single-column connectome of the Drosophila optic lobe. by Alexander Borst (32619)

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Experimental results from Diabetes dataset using Manhattan distance based matching. by Shuwen Wang (457921)

Experimental results from Spam dataset using Manhattan distance based matching. by Shuwen Wang (457921)

Network structure of perception fusion algorithm. by Weilin Wu (13736)

“…To address these issues, this paper proposes a panoramic driving perception fusion algorithm based on multi-task learning. The model training involves the introduction of different loss functions and a series of processing steps for lidar point cloud data. …”

Comparison of functions. by Shufen Niu (4423717)

Loss function and accuracy curve comparison. by Dayu Zhang (710629)

Functional validation of the metastasis-predictive genes inferred by PLUS from TCGA data. by Junyi Zhou (495644)

Graphical summary and pseudo code of our gait signatures framework and algorithm. by Taniel S. Winner (17296029)

Objective function for pressure control system. by Fazal E. Nasir (14992506)

Heterogeneity Analysis on Multi-State Brain Functional Connectivity and Adolescent Neurocognition by Shiying Wang (5179559)

“…We impose stochastic block structures to identify network-based functional phenotypes and develop a variational expectation-maximization algorithm to facilitate an efficient posterior computation. …”

Performance of ENQUIRE’s gene normalization algorithm. by Luca Musella (19986312)

Standard benchmark functions [42]. by Junhao Wei (6816803)

“…The performance of the canonical WOA is improved through innovative strategies: first, an initialization process using Good Nodes Set is introduced to ensure that the search starts from a higher-quality baseline; second, a distance-based guided search strategy is employed to adjust the search direction and intensity by calculating the distance to the optimal solution, which enhances the algorithm’s ability to escape local optima; and lastly, LSWOA introduces an enhanced spiral updating strategy, while the enhanced spiral-enveloping prey strategy effectively balances exploration and exploitation by dynamically adjusting the spiral shape parameters to adapt to different stages of the search, thereby more accurately updating the positions of individuals and improving convergence speed. …”