Modeling Decisions for Artificial Intelligence

Decision making and uncertainty.- Optimality Analysis for Stochastic LP Problems.- A Multi-Perceptual-Based Approach for Group Decision Aiding.- Probabilistic Judgement Aggregation by Opinion Update.- Semiring-valued fuzzy rough sets and colour segmentation.- Data privacy.- Bistochastic privacy.- Improvement of Estimate Distribution with Local Differential Privacy.- Geolocated Data Generation and Protection Using Generative Adversarial Net-works.- Machine Learning and data science.- A Strategic Approach based on AND-OR Recommendation Trees for Updating Obsolete Information.- Identification of Subjects Wearing a Surgical Mask from their Speech by means of x-vectors and Fisher Vectors.- Measuring Fairness in Machine Learning models via Counterfactual Examples.- Re-Calibrating Machine Learning Models using Confidence Interval Bounds.- An Analysis of Byzantine-Tolerant Aggregation Mechanisms on Model Poisoning in Federated Learning.- Effective Early Stopping of Point Cloud Neural Networks.- Representation and Interpretability of IE Integral Neural Networks.- Deep Attributed Graph Embeddings.- Estimation of Prediction Error with Regression Trees.