Modeling Decisions for Artificial Intelligence

<p>Invited Papers.- Andness-Directed Iterative OWA Aggregators.- New Eliahou semigroups and verification of the Wilf conjecture for genus up to 65.- Are Sequential Patterns Shareable? Ensuring Individuals' Privacy.- Aggregation Operators and Decision Making.- On Two Generalizations for k-additivity.- Sequential decision-making using hybrid probability-possibility functions.- Numerical comparison of idempotent andness-directed aggregators.- Approximate Reasoning.- Multiple testing of conditional independence hypotheses using information-theoretic approach.- A Bayesian Interpretation of the Monty Hall Problem with Epistemic Uncertainty.- How the F-transform can be defined for hesitant, soft or intuitionistic fuzzy sets? Enhancing social recommenders with implicit preferences and fuzzy confidence functions.- A Necessity Measure of Fuzzy Inclusion Relation in Linear Programming Problems.- Machine Learning.- Mass-based Similarity Weighted k-Neighbor for Class Imbalance.- Multinomial-based Decision Synthesis of ML Classification Outputs.- Quantile Encoder: Tackling High Cardinality Categorical Features in Regression Problems.- Evidential undersampling approach for imbalanced datasets with class-overlapping and noise.- Well-Calibrated and Sharp Interpretable Multi-Class Models.- Automated Attribute Weighting Fuzzy k-Centers Algorithm for Categorical Data Clustering.- q-Divergence Regularization of Bezdek-Type Fuzzy Clustering for Categorical Multivariate Data.- Automatic Clustering of CT Scans of COVID-19 Patients Based on Deep Learning.- Network Clustering with Controlled Node Size.- Data Science and Data Privacy.- Fair-ly Private Through Group Tagging and Relation Impact.- MEDICI: A simple to use synthetic social network data generator.- Answer Passage Ranking Enhancement Using Shallow Linguistic Features.- Neural embedded Dirichlet Processes for topic modeling.- Density-Based Evaluation Metrics in Unsupervised Anomaly Detection Contexts.- Explaining Image Misclassification in Deep Learning via Adversarial Examples.-Towards Machine Learning-Assisted Output Checking for Statistical Disclosure Control.-</p>

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