Single-cell RNA sequencing analysis reveals the expression patterns of the prognostic signature across cellular subpopulations. by Xiangxin Wu (22320058)

Integration of three machine learning algorithms to characterize lipid metabolism-associated hub genes in sepsis and atrial fibrillation. by Changze Ou (22806374)

Compare topologies when using the WOA algorithm to solve the RNP problem by different methods. by Le Huu Binh (18340233)

Compare topologies when using the MVO algorithm to solve the RNP problem by different methods. by Le Huu Binh (18340233)

archive.zip by Tasneem Fatima (21976946)

Loss function comparison plot. by Wenhao Ren (2561731)

-value on 23 benchmark functions (dim = 30). by Yuqi Xiong (12343771)

“…<div><p>Metaheuristic optimization algorithms often face challenges such as complex modeling, limited adaptability, and a tendency to get trapped in local optima when solving complex optimization problems. …”

Flow chart diagram of blind quantum algorithm. by Sultan H. Almotiri (14029251)

“…However, in the pursuit of complexity, vulnerabilities may be introduced inadvertently, posing a substantial danger to software security. Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

A robust privacy-preserving online monitoring algorithm for disease surveillance by Miaomiao Yu (519470)

“…Further, we introduce an adaptive estimation method and a weighting function to reduce the sensitivity loss in the monitoring and robustness loss in the private monitoring algorithm. …”

Confusion matrices depict the performance of various ML algorithms. by Caroline L. Alves (14271413)

Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms by Saadiallakh Normatov (20682324)

Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms by Saadiallakh Normatov (20682324)

Rosenbrock function losses for . by 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 . by 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 . by 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 . by 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 . by 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 . by 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 . by 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 . by 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. …”