Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level حسب Giovanni Nattino (561797)

"…We fill the gap by developing an iterative matching algorithm for the three-group setting. Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …"

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses حسب Meichen Liu (8168148)

Latin sampling. حسب Honghua Liu (15307022)

AUW-CE Mining Algorithms & Dataset Hub حسب Shuaikang Yuan (21091847)

"…Moreover, in response to the limitations of conventional cross-entropy methods for HUCPM, four core optimization strategies are designed: optimization of the initial probability distribution to guide the search direction, enhancement of sample diversity to prevent local convergence, dynamic adjustment of sample size to reduce redundant calculations, and incorporation of utility weights to improve the accuracy of probability updates. …"

NucB sampling: حسب Carlos A. Gomez-Uribe (21492788)

Alpha amylase sampling: حسب Carlos A. Gomez-Uribe (21492788)

PANet network design. حسب Mengqi Yuan (4852555)

"…Second, a dynamic up-sampling technique was introduced to improve the model’s ability to recover fine details. …"

BiFPN network design. حسب Mengqi Yuan (4852555)

"…Second, a dynamic up-sampling technique was introduced to improve the model’s ability to recover fine details. …"

Accelerated Design for High-Entropy Alloys Based on Machine Learning and Multiobjective Optimization حسب Yingying Ma (3617810)

"…Notably, the <i>D</i> of three candidates have shown significant improvements compared to the samples with similar <i>H</i> in the original data sets, with increases of 135.8, 282.4, and 194.1% respectively. …"

Accelerated Design for High-Entropy Alloys Based on Machine Learning and Multiobjective Optimization حسب Yingying Ma (3617810)

"…Notably, the <i>D</i> of three candidates have shown significant improvements compared to the samples with similar <i>H</i> in the original data sets, with increases of 135.8, 282.4, and 194.1% respectively. …"

Algorithm for generating hyperparameter. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"

Performance of the optimal classifiers on each feature list. حسب Wenwei Wu (9352541)

Data_Sheet_1_Critical Evaluation of Metaheuristic Algorithms for Weight Minimization of Truss Structures.docx حسب Aristotelis E. Charalampakis (7454258)

Three sensor sample data with noise data. حسب Tang Ruipeng (20141334)

Results of machine learning algorithm. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"

Third setting: batch optimization. حسب Camille Gontier (9442304)

Policy network (<i>θ</i>′) of SAM to accommodate PPO algorithm. حسب Zhenhan Huang (12107002)

ROC comparison of machine learning algorithm. حسب Balraj Preet Kaur (20370832)

"…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"

Code and data for Lambert and Ellner, "SDM meets eDNA: optimal sampling of environmental DNA to estimate species-environment relationships in stream networks", Ecography (2025) حسب Timothy Lambert (16890087)

"…The code includes: (1) an iterative generalized least squares solution method for estimating model parameters, (2) a genetic algorithm for finding D-optimal sampling designs (i.e., the positioning of samples on a stream network that most accurately estimates species-environment relationships), and (3) generalized additive models for estimating the dependence of estimation accuracy on a stream network's topological and hydrologic properties.…"

Upset graph to show the intersection of features used in three optimal classifiers. حسب Wenwei Wu (9352541)