Modeling Decisions for Artificial Intelligence

Logic Aggregators and Their Implementations.- Decision making and uncertainty.- Multi-Target Decision Making under Conditions of Severe Uncertainty.- Constructive set function and extraction of a k-dimensional element.- Coherent upper conditional previsions defined by fractal outer measures to represent the unconscious activity of human brain.- Discrete chain-based Choquet-like operators.- On a new generalization of decomposition integrals.- Bipolar OWA operators with continuous input function.- Machine Learning and data science.- Cost-constrained group feature selection using information theory.- Conformal Prediction for Accuracy Guarantees in Classification with Reject Option.- Adapting the Gini's index for solving Predictive Tasks.- Bayesian logistic model for positive and unlabeled data.- A goal-oriented specification language for reinforcement learning.- Improved Spectral Norm Regularization for NeuralNetworks.- Preprocessing Matters: Automated Pipeline Selection for Fair Classification.- Predicting Next Whereabouts using Deep Learning.- A Generalization of Fuzzy c-Means with Variables Controlling Cluster Size.- Data privacy.- Local Differential Privacy Protocol for Making Key{Value Data Robust against Poisoning Attacks.- Differential Privacy through Noise-Graph Addition.