Modeling Decisions for Artificial Intelligence : 21st International Conference, MDAI 2024, Tokyo, Japan, August 27–31, 2024, Proceedings / edited by Vicenç Torra, Yasuo Narukawa, Hiroaki Kikuchi.

Format:

Book

Contributor:

Torra, Vicenç, editor.

Narukawa, Yasuo, editor.

Kikuchi, Hiroaki, editor.

Series:

Lecture Notes in Artificial Intelligence, 2945-9141 ; 14986

Language:

English

Subjects (All):

Artificial intelligence.

Computer systems.

Computer networks.

Data structures (Computer science).

Information theory.

Computer science.

Artificial Intelligence.

Computer System Implementation.

Computer Communication Networks.

Data Structures and Information Theory.

Theory of Computation.

Local Subjects:

Artificial Intelligence.

Computer System Implementation.

Computer Communication Networks.

Data Structures and Information Theory.

Theory of Computation.

Physical Description:

1 online resource (257 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

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.

Contents:

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.

Notes:

Includes bibliographical references and index.

ISBN:

3-031-68208-4