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Titlebook: Reasoning Web. Causality, Explanations and Declarative Knowledge; 18th International S Leopoldo Bertossi,Guohui Xiao Textbook 2023 The Edit

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發(fā)表于 2025-3-21 19:26:11 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Reasoning Web. Causality, Explanations and Declarative Knowledge
副標題18th International S
編輯Leopoldo Bertossi,Guohui Xiao
視頻videohttp://file.papertrans.cn/823/822475/822475.mp4
概述Useful for students, researchers, and practitioners.Lecturers are known experts in this field.Declarative Artificial Intelligence
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Reasoning Web. Causality, Explanations and Declarative Knowledge; 18th International S Leopoldo Bertossi,Guohui Xiao Textbook 2023 The Edit
描述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
出版日期Textbook 2023
關鍵詞Computer Science; Informatics; Conference Proceedings; Research; Applications
版次1
doihttps://doi.org/10.1007/978-3-031-31414-8
isbn_softcover978-3-031-31413-1
isbn_ebook978-3-031-31414-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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發(fā)表于 2025-3-22 00:14:25 | 只看該作者
,Causal Inference in?Data Analysis with?Applications to?Fairness and?Explanations,ta from the AI and Statistics literature. Furthermore, we discuss how concepts from causal inference can be used to infer fairness and enable explainability in machine learning models, which are critical in responsible data science when ML is used in making high-stake decisions in various contexts.
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Vadalog: Overview, Extensions and Business Applications, a basic overview, including an introduction to dependencies, the Datalog and Vadalog languages, (2) the extensions of the system, including arithmetic and aggregation, real-world data interfaces, temporal reasoning, and machine learning, and (3) the business applications, including: corporate gover
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Textbook 2023ons 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
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Reasoning Web. Causality, Explanations and Declarative Knowledge18th International S
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Teodoro Baldazzi,Luigi Bellomarini,Markus Gerschberger,Aditya Jami,Davide Magnanimi,Markus Nissl,Alesieht, wie es gesehen werden und wohin es sich entwickeln m?chte. Diese Vision muss durch drei Elemente untermauert werden, die ihr erst die notwendige Klarheit und Glaubwürdigkeit verleihen! Erstens: Die Vision sollte auf einer klaren Mission aufbauen, die den eigenen Anspruch und Auftrag des Unter
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