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E-raamat: Modeling Decisions for Artificial Intelligence: 21st International Conference, MDAI 2024, Tokyo, Japan, August 27-31, 2024, Proceedings

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Modeling Decisions for Artificial Intelligence: 21st International Conference, MDAI 2024, Tokyo, Japan, August 27-31, 2024, ProceedingsSuurem pilt
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This book constitutes the refereed proceedings of the 21st International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2024, held in Umeå, Sweden, during August 27-30, 2024.





The 18 full papers were carefully reviewed and selected from 37 submissions. There were organized in topical headings as follows: Fuzzy measures and integrals; uncertainty in AI; clustering; and data science and data privacy.
Invited paper.- Taste Media Innovative Technology Transforms the Eating
Experience.- Fuzzy measures and integrals.- An axiomatic definition of non
discrete Mbius transform.- Fuzzy Rough Choquet Distances.- Uncertainty in
AI.- Entropies from f divergences.- Comparative Study of Methods for
Estimating Interval Priority Weights Focusing on the Accuracy in Selecting
the Best Alternative.- Clustering.- Sequential Cluster Extraction by Noise
Clustering Based on Local Outlier Factor.- On Objective Based Clustering from
the Perspective of Transportation Problem.- Data science and data privacy.-
Decision Tree Based Inference of Lightning Network Client Implementations.-
nuggets Data Pattern Extraction Framework in R.- User centred Argumentation
Analysis of Local Explanations in Explainable AI.- Revised
Margin-Maximization Method for Fuzzy Nearest Prototype Classification.-
Bistochastically private release of data streams with delay.- Differentially
Private Extreme Learning Machine.- Studying the impact of edge privacy on
link prediction in temporal graphs.- Dissimilar Similarities Comparing Human
and Statistical Similarity Evaluation in Medical AI.- On the necessity of
counterfeits and deletions for continuous data publishing.- A
Poisoning-Resilient LDP schema leveraging Oblivious Transfer with the
Hadamard Transform.- Experimental Evaluation for Risk Assessment of Privacy
Preserving Synthetic Data.- Transforming Stock Price Forecasting Deep
Learning Architectures and Strategic Feature Engineering.
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