Modeling Decisions for Artificial Intelligence (eBook, PDF)

21st International Conference, MDAI 2024, Tokyo, Japan, August 27-31, 2024, Proceedings
Redaktion: Torra, Vicenç; Kikuchi, Hiroaki; Narukawa, Yasuo

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 252
• Erscheinungstermin: 14. August 2024
• Englisch
• ISBN-13: 9783031682087
• Artikelnr.: 72243267

Inhaltsangabe

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.