Foundations of Intelligent Systems

.- Classification and Clustering.

.- Improving the robustness to color perturbations of classification and regression models in the visual evaluation of fruits and vegetables.

.- Clustering Under Radius Constraints Using Minimum Dominating Sets.

.- Learning Typicality Inclusions in a Probabilistic Description Logic for Concept Combination.

.- Neural Network and Natural Language Processing.

.- LLMental Classification of mental disorders with large language models.

.- CSEPrompts A Benchmark of Introductory Computer Science Prompts.

.- Semantically-Informed Domain Adaptation for Named Entity Recognition.

.- Token Pruning by Dimensionality Reduction Methods on TCT Colbert for Reranking.

.- AI Tools and Models.

.- Exploiting microRNA expression data for the diagnosis of disease conditions and the discovery of novel biomarkers.

.- HERSE: Handling and Enhancing RDF Summarization through blank node Elimination.

.- Rough Sets For a Neuromorphic CMOS System.

.- Neural Network and Data Mining.

.- Erasing the Shadow Sanitization of Images with Malicious Payloads using Deep Autoencoders.

.- Digilog Enhancing Website Embedding on Local Governments - A Comparative Analysis.

.- A Stream Data Mining Approach to Handle Concept Drifts in Process Discovery.

.- Explainability in AI.

.- Enhancing temporal Transformers for financial time series via local surrogate interpretability.

.- Explaining commonalities of clusters of RDF resources in natural language.

.- Shapley-Based Data Valuation Method for the Machine Learning Data Markets (MLDM).

.- Industry Session.

.- ScoredKNN: An Efficient KNN Recommender based on Dimensionality Reduction for Big Data.