Coherent upper conditional previsions defined by fractal outer measures to represent the unconscious activity of human brain

The proceedings contain 18 papers. The special focus in this conference is on Modeling Decisions for Artificial Intelligence. The topics include: Bayesian Logistic Model for Positive and Unlabeled Data; a Goal-Oriented Specification Language for Reinforcement Learning; improved Spectral Norm Regularization for Neural Networks; 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; local Differential Privacy Protocol for Making Key–Value Data Robust Against Poisoning Attacks; differentially Private Graph Publishing Through Noise-Graph Addition; 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; cost-constrained Group Feature Selection Using Information Theory; conformal Prediction for Accuracy Guarantees in Classification with Reject Option.