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Reasoning web. causality, explanations and declarative knowledge18th International Summer School 2022, Berlin, Germany, September 27-30, 2022 : tutorial lectures /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Reasoning web. causality, explanations and declarative knowledgeedited by Leopoldo Bertossi, Guohui Xiao.
Reminder of title:	18th International Summer School 2022, Berlin, Germany, September 27-30, 2022 : tutorial lectures /
other author:	Bertossi, Leopoldo.
corporate name:
Published:	Cham :Springer Nature Switzerland :2023.
Description:	ix, 211 p. :ill. (some col.), digital ;24 cm.
Notes:	"It was held online due to anticipated mobility restrictions caused by the Covid-19 pandemic."-- Preface.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence
Online resource:	https://doi.org/10.1007/978-3-031-31414-8
ISBN:	9783031314148$q(electronic bk.)

Reasoning web. causality, explanations and declarative knowledge18th International Summer School 2022, Berlin, Germany, September 27-30, 2022 : tutorial lectures /
Reasoning web. causality, explanations and declarative knowledge18th International Summer School 2022, Berlin, Germany, September 27-30, 2022 : tutorial lectures /[electronic resource] :edited by Leopoldo Bertossi, Guohui Xiao. - Cham :Springer Nature Switzerland :2023. - ix, 211 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,137590302-9743 ;. - Lecture notes in computer science ;4891..

"It was held online due to anticipated mobility restrictions caused by the Covid-19 pandemic."-- Preface.

Explainability in Machine Learning -- Causal Explanations and Fairness in Data -- Statistical Relational Extensions of Answer Set Programming -- Vadalog: Its Extensions and Business Applications -- Cross-Modal Knowledge Discovery, Inference, and Challenges -- Reasoning with Tractable Probabilistic Circuits -- From Statistical Relational to Neural Symbolic Artificial Intelligence -- Building Intelligent Data Apps in Rel using Reasoning and Probabilistic Modelling.

The purpose of the Reasoning Web Summer School is to disseminate recent advances on reasoning techniques and related issues that are of particular interest to Semantic Web and Linked Data applications. It is primarily intended for postgraduate students, postdocs, young researchers, and senior researchers wishing to deepen their knowledge. As in the previous years, lectures in the summer school were given by a distinguished group of expert lecturers. The broad theme of this year's summer school was "Reasoning in Probabilistic Models and Machine Learning" and it covered various aspects of ontological reasoning and related issues that are of particular interest to Semantic Web and Linked Data applications. The following eight lectures were presented during the school: Logic-Based Explainability in Machine Learning; Causal Explanations and Fairness in Data; Statistical Relational Extensions of Answer Set Programming; Vadalog: Its Extensions and Business Applications; Cross-Modal Knowledge Discovery, Inference, and Challenges; Reasoning with Tractable Probabilistic Circuits; From Statistical Relational to Neural Symbolic Artificial Intelligence; Building Intelligent Data Apps in Rel using Reasoning and Probabilistic Modelling.

ISBN: 9783031314148$q(electronic bk.)

Standard No.: 10.1007/978-3-031-31414-8doiSubjects--Topical Terms:

252958
Artificial intelligence

LC Class. No.: Q334 / .S86 2022

Dewey Class. No.: 006.3

Reasoning web. causality, explanations and declarative knowledge18th International Summer School 2022, Berlin, Germany, September 27-30, 2022 : tutorial lectures /
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520 $a The purpose of the Reasoning Web Summer School is to disseminate recent advances on reasoning techniques and related issues that are of particular interest to Semantic Web and Linked Data applications. It is primarily intended for postgraduate students, postdocs, young researchers, and senior researchers wishing to deepen their knowledge. As in the previous years, lectures in the summer school were given by a distinguished group of expert lecturers. The broad theme of this year's summer school was "Reasoning in Probabilistic Models and Machine Learning" and it covered various aspects of ontological reasoning and related issues that are of particular interest to Semantic Web and Linked Data applications. The following eight lectures were presented during the school: Logic-Based Explainability in Machine Learning; Causal Explanations and Fairness in Data; Statistical Relational Extensions of Answer Set Programming; Vadalog: Its Extensions and Business Applications; Cross-Modal Knowledge Discovery, Inference, and Challenges; Reasoning with Tractable Probabilistic Circuits; From Statistical Relational to Neural Symbolic Artificial Intelligence; Building Intelligent Data Apps in Rel using Reasoning and Probabilistic Modelling.
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