Training process of HFKG-RFE algorithm. by Chunjuan Li (7890182)

“…Therefore, An Algorithm for Heterogeneous Federated Knowledge Graph (HFKG) is proposed to solve this problem by limiting model drift through comparative learning. …”

Convergence curves for all algorithms. by Genliang Li (5816264)

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Parameter Settings for competitive algorithms. by Genliang Li (5816264)

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Proposed Algorithm. by Hend Bayoumi (22693738)

“…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. …”

The flow chart of the IES program solved by the MSAGOOSE algorithm. by Chengcheng Ding (9013862)

Metaheuristic algorithms for solving DNA-related problems. by Eslam Hamouda (5172083)

Details of multiple GWO algorithm variants. by Genliang Li (5816264)

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Data embedding by using Neural Quantum Embedding (NQE). by Aninda Astuti (21736334)

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Algorithm process. by Wei Cui (92129)

The pre-processing of CTG raw signals [26]. by Amin Ullah (12015113)

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Classification performance results using 5-fold cross-validation for the training datasets after applying the data imbalance tool, SMOTE and NQE for data embedding. The values with... by Aninda Astuti (21736334)

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Classification performance results using 5-fold cross-validation for the training datasets after applying the data imbalance tool, SMOTE and NQE for data embedding. The values with... by Aninda Astuti (21736334)

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The PCA plots of the data distribution (mRNA) projected onto two principal components selected from PC1 through PC12. by Aninda Astuti (21736334)

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The PCA plots of the data distribution (mRNA) projected onto two principal components selected from PC1 through PC11. by Aninda Astuti (21736334)

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The PCA plots of the data distribution (mRNA) projected onto two principal components selected from PC1 through PC10. by Aninda Astuti (21736334)

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Comparison of performance metrics, SVC vs QSVC after using NQE for data embedding. Bold-faced fonts denote that the classifier achieves better performance. by Aninda Astuti (21736334)

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Comparison of NQE combined with SVC, NN, and QCNN classifiers. The table shows the number of test cases, comparison with classical classifiers, and data imbalance issues in this an... by Aninda Astuti (21736334)

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The Search process of the genetic algorithm. by Wenguang Li (6528113)

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Enhancing off-policy optimisation in structured Markov decision processes via Thompson Sampling by Sourav Ganguly (293262)

“…<p>Reinforcement Learning (RL) provides a framework for solving sequential decision-making tasks, yet limited and potentially unsafe data hinder its training process. …”

Deep reinforcement learning agents trained using a curriculum solve navigation tasks with delayed rewards. by William L. Tong (22238845)