The optimization result of 10 benchmark functions for different algorithms (D = 10). by Yu Li (183836)

The optimization result of 10 benchmark functions for different algorithms (D = 30). by Yu Li (183836)

The result of CEC2010 standard functions for different algorithms (D = 30). by Yu Li (183836)

The optimization result of 10 benchmark functions for different algorithms (D = 100). by Yu Li (183836)

The convergence curves of the function in different dimensions. by Yu Li (183836)

Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

Subjects:

Functional effect prediction of FUS mutations by ten nsSNP prediction algorithms. by L. F. S. Bonet (11502082)

Convergence curves of multimodal functions <i>f</i>₇. by Yu Li (183836)

Convergence curves of unimodal functions <i>f</i>₂. by Yu Li (183836)

Convergence curves of unimodal functions <i>f</i>₂. by Yu Li (183836)

Convergence curves of multimodal functions <i>f</i>₇. by Yu Li (183836)

Objective function value statistics. by Chao Li (145513)

Heat maps of mean scores over 50 datasets of the algorithms as a function of relative noise and number of samples. by Yuanchen Zhao (12905580)

Subjects:

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

Subjects:

Flowchart of system algorithm. by Syed Zahurul Islam (9635163)

Comparison with the BST algorithm for the AF and CST bundles. by Thomas Durantel (20933812)

Subjects:

Model selection for machine learning algorithm based on microbial abundances. by Elio L. Herzog (11576876)

Subjects: “…applying independent algorithms…”

Convergence curve of functions <i>f</i>_<i>1</i><i>-f</i>_<i>10</i> in D = 10. by Yu Li (183836)

Flowchart of step() function. by Raed Alharthi (18340157)

Coarse-fine optimization algorithm. by Chao Ma (207385)

“…The improved gradient extraction method combines the Scale Invariant Feature Transformation (SIFT) algorithm to form a new multi-scale image sharpness evaluation function, SIFT Quad-Tenen. …”