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Explainable Artificial Intelligence: First World Conference, xAI 2023, Lisbon, Portugal, July 26–28, 2023, Proceedings, Part I: Communications in Computer and Information Science, cartea 1901

Editat de Luca Longo
en Limba Engleză Paperback – 30 oct 2023
This three-volume set constitutes the refereed proceedings of the First World Conference on Explainable Artificial Intelligence, xAI 2023, held in Lisbon, Portugal, in July 2023. 

The 94 papers presented were thoroughly reviewed and selected from the 220 qualified submissions. They are organized in the following topical sections: ​

Part I: Interdisciplinary perspectives, approaches and strategies for xAI; Model-agnostic explanations, methods and techniques for xAI, Causality and Explainable AI; Explainable AI in Finance, cybersecurity, health-care and biomedicine.

Part II: Surveys, benchmarks, visual representations and applications for xAI; xAI for decision-making and human-AI collaboration, for Machine Learning on Graphs with Ontologies and Graph Neural Networks; Actionable eXplainable AI, Semantics and explainability, and Explanations for Advice-Giving Systems.

Part III: xAI for time series and Natural Language Processing; Human-centered explanations and xAI for Trustworthy and Responsible AI; Explainable and Interpretable AI with Argumentation, Representational Learning and concept extraction for xAI.
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Specificații

ISBN-13: 9783031440632
ISBN-10: 3031440633
Pagini: 692
Ilustrații: XXV, 692 p. 198 illus., 158 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.99 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Cham, Switzerland

Cuprins

Interdisciplinary perspectives, approaches and strategies for xAI.- Model-agnostic explanations, methods and techniques for xAI, Causality and Explainable AI.- Explainable AI in Finance, cybersecurity, health-care and biomedicine.

Textul de pe ultima copertă

Chapters “Finding Spurious Correlations with Function-Semantic Contrast Analysis” and “Explaining Socio-Demographic and Behavioral Patterns of Vaccination Against the Swine Flu (H1N1) Pandemic” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.