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E-raamat: Modeling Decisions for Artificial Intelligence: 18th International Conference, MDAI 2021, Umea, Sweden, September 27-30, 2021, Proceedings

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Modeling Decisions for Artificial Intelligence: 18th International Conference, MDAI 2021, Umea, Sweden, September 27-30, 2021, ProceedingsSuurem pilt
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This book constitutes the refereed proceedings of the 18th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2021, held in Umeå, Sweden, in September 2021.*





The 24 papers presented in this volume were carefully reviewed and selected from 50 submissions. Additionally, 3 invited papers were included. The papers discuss different facets of decision processes in a broad sense and present research in data science, data privacy, aggregation functions, human decision making, graphs and social networks, and recommendation and search. The papers are organized in the following topical sections: aggregation operators and decision making; approximate reasoning; machine learning; data science and data privacy.





*The conference was held virtually due to the COVID-19 pandemic.
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.-



 
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