Accurate prediction of learner performance is essential for adaptive educational systems and personalized learning. However, the integration of advanced gradient-boosting models with established educational frameworks remains underexplored, particularly when predictive performance and interpretability are considered jo...
Zakaria Alj, A. Bouayad· Frontiers in Artificial Inte...· 0 citations
Key findings reveal that current solutions remain fragmented across sensing, fusion, adaptation, and privacy dimensions, and that future research must prioritize unified frameworks jointly addressing multimodal fusion, continual adaptation, edge inference, privacy preservation, and explainability.
Z. Lazrak, A. Bouayad, Marwa Boumaiz· Discover Artificial Intellig...· 0 citations
Deep neural networks often achieve high accuracy, but their compute, memory, and power demands can hinder deployment on resource-constrained edge devices. This paper proposes an iterative, constraint-aware knowledge distillation framework that compresses a large model into a small one under an explicit model-size budge...
Mohamed Echchidmi, Anas Bouayad· IEEE International Conferenc...· 0 citations
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