Comparisons of 90% credible intervals (CIs) for off-diagonal elements of precision matrix Ω. by Aapo E. Korhonen (22530674)

Path data for different algorithms in four different environments. by Tengfei Ma (597633)

Federated averaging algorithm pseudocode. by Hadi Mohammadian KhalafAnsar (22783784)

IbM code graphical description by Irina Ofiteru (14716360)

Pseudo-code for the study design model. by Jianpeng Zhang (528185)

The algorithm of the applied models. by Elif Tuçe Bal (21367965)

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Federated Mixture of experts Correction Algorithm. by Ruizhi Yuan (16864629)

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Federated Maximum Diversity Clustering Algorithm. by Ruizhi Yuan (16864629)

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Source Code for Comparative Study of Search Trees Implemented in Java by Mohammed Alaa Ala'anzy (21711464)

Comparison of machine learning algorithm results for N-gram + grayscale value frequency features. by Daowei Chen (9077770)

Comparison between Deep and Machine Learning algorithms (MAE and MSE lower the better) [25]. by Marco Alderighi (7195721)

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Comparison of machine learning algorithm results for N-gram + grayscale value frequency features. by Daowei Chen (9077770)

Statistic results between the proposed algorithm and other metaheuristic algorithms. by ZeSheng Lin (20501356)

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Data Sheet 2_Mitochondrial non-coding RNAs as novel biomarkers and therapeutic targets in lung cancer integration of traditional bioinformatics and machine learning approaches.csv by Liu Haoming (22524473)

“…Machine learning algorithms (SVM, Random Forest, Logistic Regression) classified samples using differentially expressed mtRNAs (P < 0.01, |log2FC| > 1). …”

Data Sheet 1_Mitochondrial non-coding RNAs as novel biomarkers and therapeutic targets in lung cancer integration of traditional bioinformatics and machine learning approaches.csv by Liu Haoming (22524473)

“…Machine learning algorithms (SVM, Random Forest, Logistic Regression) classified samples using differentially expressed mtRNAs (P < 0.01, |log2FC| > 1). …”

The proposed algorithm of the outlier detection method. by Sunil Kumar (102321)

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Hyperspectral Camouflage Detection Dataset and Codes by Qiran Wang (22051883)

“…This study proposes a non-destructive classification framework integrating optimized sample partitioning, spectral preprocessing, and residual deep learning to address this challenge. Hyperspectral data of camouflage fabrics and natural grass (389.06–1005.10 nm) were acquired and preprocessed using principal component analysis, standard normal variate transformation, Savitzky–Golay filtering, and derivative-based enhancement. …”

List of the time used by each algorithm. by JiaMing Gong (20427837)

“…To this end, this paper proposes an entropy-based dynamic ensemble classification algorithm (EDAC) to consider data streams with class imbalance and concept drift simultaneously. …”

Data Sheet 1_A combined model of shoot phosphorus uptake based on sparse data and active learning algorithm.pdf by Tianli Wang (1438498)

data and code by PENGCHENG LIU (20680641)

“…Combined with the road network data, this algorithm regards the trajectory data as a signal that changes dynamically with time, converts it from time domain to frequency domain through Fourier transform, fits the trajectory points in the spectrum domain, and converts the discrete trajectory points into time continuous line elements.…”