Modeling Decisions for Artificial Intelligence 17th International Conference MDAI 2020 Sant Cugat Spain September 2 4 2020 Proceedings 1st Edition by Vicenç Torra, Yasuo Narukawa, Jordi Nin, Núria Agell ISBN 3030575233 978-3030575236

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Product details:

ISBN 10: 3030575233

ISBN 13:  978-3030575236

Author: Vicenç Torra, Yasuo Narukawa, Jordi Nin, Núria Agell

This book constitutes the refereed proceedings of the 17th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2020, held in Sant Cugat, Spain, in September 2020.*

The 24 papers presented in this volume were carefully reviewed and selected from 46 submissions. They 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, and data science and data mining.

Table of contents: 

1. A Characterization of Belief Merging Operators in the Regular Horn Fragment of Signed Logic

2. Bivariate Risk Measures and Stochastic Orders

3. Stochastic Orders on Two-Dimensional Space: Application to Cross Entropy

4. Modeling Decisions in AI: Re-thinking Linda in Terms of Coherent Lower and Upper Conditional Previsions

5. Ensemble Learning, Social Choice and Collective Intelligence

6. An Unsupervised Capacity Identification Approach Based on Sobol’ Indices

7. Probabilistic Measures and Integrals: How to Aggregate Imprecise Data

8. Distorted Probabilities and Bayesian Confirmation Measures

9. Constructive k-Additive Measure and Decreasing Convergence Theorems

10. Generalization Property of Fuzzy Classification Function for Tsallis Entropy-Regularization of Bezdek-Type Fuzzy C-Means Clustering

11. Nonparametric Bayesian Nonnegative Matrix Factorization

12. SentiRank: A System to Integrate Aspect-Based Sentiment Analysis and Multi-criteria Decision Support

13. Efficient Detection of Byzantine Attacks in Federated Learning Using Last Layer Biases

14. Multi-object Tracking Combines Motion and Visual Information

15. Classifying Candidate Axioms via Dimensionality Reduction Techniques

16. Sampling Unknown Decision Functions to Build Classifier Copies

17. Towards Analogy-Based Explanations in Machine Learning

18. An Improved Bi-level Multi-objective Evolutionary Algorithm for the Production-Distribution Planning System

19. Modifying the Symbolic Aggregate Approximation Method to Capture Segment Trend Information

20. Efficiently Mining Gapped and Window Constraint Frequent Sequential Patterns

21. Aggregating News Reporting Sentiment by Means of Hesitant Linguistic Terms

22. Decision Trees as a Tool for Data Analysis. Elections in Barcelona: A Case Study

23. Explaining Misclassification and Attacks in Deep Learning via Random Forests

24. Fair-MDAV: An Algorithm for Fair Privacy by Microaggregation

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Tags: Vicenç Torra, Yasuo Narukawa, Jordi Nin, Núria Agell, Modeling Decisions, Artificial Intelligence, International Conference