Reasoning Web. Causality, Explanations and Declarative Knowledge: 18th International Summer School 2022, Berlin, Germany, September 27–30, 2022, Tutorial Lectures
Leopoldo Bertossi · Guohui Xiao
apr. 2023 · Springer Nature
E-knjiga
211
Strani
reportOcene in mnenja niso preverjeni. Več o tem
O tej e-knjigi
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.
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.
O avtorju
Leopoldo Bertossi,
Skema Business School, Montreal, Canada
Skema Business School, Montreal, Canada
Guohui Xiao
University of Bergen, Bergen, Norway
Ocenite to e-knjigo
Povejte nam svoje mnenje.
Informacije o branju
Pametni telefoni in tablični računalniki
Namestite aplikacijo Knjige Google Play za Android in iPad/iPhone. Samodejno se sinhronizira z računom in kjer koli omogoča branje s povezavo ali brez nje.
Prenosni in namizni računalniki
Poslušate lahko zvočne knjige, ki ste jih kupili v Googlu Play v brskalniku računalnika.
Bralniki e-knjig in druge naprave
Če želite brati v napravah, ki imajo zaslone z e-črnilom, kot so e-bralniki Kobo, morate prenesti datoteko in jo kopirati v napravo. Podrobna navodila za prenos datotek v podprte bralnike e-knjig najdete v centru za pomoč.
