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Modeling Decisions for Artificial Intelligence: 21st International Conference, MDAI 2024, Tokyo, Japan, September 3–6, 2024, Proceedings de Vicenç Torra

Modeling Decisions for Artificial Intelligence: 21st International Conference, MDAI 2024, Tokyo, Japan, September 3–6, 2024, Proceedings: Lecture Notes in Computer Science, cartea 14986

Editat de Vicenç Torra, Yasuo Narukawa, Hiroaki Kikuchi
en Limba Engleză Paperback – 22 sep 2024
This book constitutes the refereed proceedings of the 21st International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2024, held in Umeå, Sweden, during September 3-6, 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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Specificații

ISBN-13: 9783031682070
ISBN-10: 3031682076
Ilustrații: XII, 193 p.
Dimensiuni: 155 x 235 mm
Ediția:2024
Editura: Springer Nature Switzerland
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence

Locul publicării:Cham, Switzerland

Cuprins

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.