Hierarchical Optimization on large models. حسب Nisha Ann Viswan (20371285)

Dropout optimization model framework structure diagram. حسب Peng Yang (296696)

An optimal solution for the HFS instance. حسب Xiang Tian (4369285)

"…Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …"

Face recognition algorithm flow based on the PCA. حسب Na Lin (69470)

Proposed Algorithm. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Flat optimization method. حسب Nisha Ann Viswan (20371285)

ReaLigands: A Ligand Library Cultivated from Experiment and Intended for Molecular Computational Catalyst Design حسب Shu-Sen Chen (1777108)

"…Individual ligands from mononuclear crystal structures were identified using a modified depth-first search algorithm and charge was assigned using a machine learning model based on quantum-chemical calculated features. …"

Comparisons between ADAM and NADAM optimizers. حسب Hend Bayoumi (22693738)

"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

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

Schematic diagram of the Dropout optimization. حسب Peng Yang (296696)

Comparison based on hard instances from [79]. حسب Xiang Tian (4369285)

"…Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …"

Image 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.tif حسب Xuehui Fan (10762662)

ROC curves of different models. حسب Yan Liu (25061)

Changes in loss curves of different models. حسب Yan Liu (25061)

Feature matching errors of different models. حسب Yan Liu (25061)

Data Sheet 7_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

Data Sheet 2_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

Data Sheet 9_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.xlsx حسب Xuehui Fan (10762662)

Data Sheet 5_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

Data Sheet 8_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)