Homomorphic binary tree. حسب Jianhua He (341366)

Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. حسب Tristan Mary-Huard (3864)

Hyperparameters of the LSTM Model. حسب Ahmed M. Elshewey (21463867)

"…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"

The AD-PSO-Guided WOA LSTM framework. حسب Ahmed M. Elshewey (21463867)

"…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"

Prediction results of individual models. حسب Ahmed M. Elshewey (21463867)

"…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"

Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes حسب Yu Y. (3096192)

"…We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …"

Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods حسب Jiacong Du (12035845)

"…Building on existing work, we (i) derive and implement efficient cyclic coordinate descent and majorization-minimization optimization algorithms for continuous and binary outcome data, (ii) incorporate adaptive shrinkage penalties, (iii) compare these methods through simulation, and (iv) develop an R package <i>miselect</i>. …"