Building Bridges Between Soft and Statistical Methodologies for Data Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Building Bridges Between Soft and Statistical Methodologies for Data Science write by Luis A. García-Escudero. This book was released on 2023. Building Bridges Between Soft and Statistical Methodologies for Data Science available in PDF, EPUB and Kindle. Nowadays, data analysis is becoming an appealing topic due to the emergence of new data types, dimensions, and sources. This motivates the development of probabilistic/statistical approaches and tools to cope with these data. Different communities of experts, namely statisticians, mathematicians, computer scientists, engineers, econometricians, and psychologists are more and more interested in facing this challenge. As a consequence, there is a clear need to build bridges between all these communities for Data Science. This book contains more than fifty selected recent contributions aiming to establish the above referred bridges. These contributions address very different and relevant aspects such as imprecise probabilities, information theory, random sets and random fuzzy sets, belief functions, possibility theory, dependence modelling and copulas, clustering, depth concepts, dimensionality reduction of complex data and robustness.
Building Bridges between Soft and Statistical Methodologies for Data Science
Building Bridges between Soft and Statistical Methodologies for Data Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Building Bridges between Soft and Statistical Methodologies for Data Science write by Luis A. García-Escudero. This book was released on 2022-08-24. Building Bridges between Soft and Statistical Methodologies for Data Science available in PDF, EPUB and Kindle. Nowadays, data analysis is becoming an appealing topic due to the emergence of new data types, dimensions, and sources. This motivates the development of probabilistic/statistical approaches and tools to cope with these data. Different communities of experts, namely statisticians, mathematicians, computer scientists, engineers, econometricians, and psychologists are more and more interested in facing this challenge. As a consequence, there is a clear need to build bridges between all these communities for Data Science. This book contains more than fifty selected recent contributions aiming to establish the above referred bridges. These contributions address very different and relevant aspects such as imprecise probabilities, information theory, random sets and random fuzzy sets, belief functions, possibility theory, dependence modelling and copulas, clustering, depth concepts, dimensionality reduction of complex data and robustness.
Combining, Modelling and Analyzing Imprecision, Randomness and Dependence
Combining, Modelling and Analyzing Imprecision, Randomness and Dependence - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Combining, Modelling and Analyzing Imprecision, Randomness and Dependence write by Jonathan Ansari. This book was released on . Combining, Modelling and Analyzing Imprecision, Randomness and Dependence available in PDF, EPUB and Kindle.
Reasoning Web. Causality, Explanations and Declarative Knowledge
Reasoning Web. Causality, Explanations and Declarative Knowledge - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Reasoning Web. Causality, Explanations and Declarative Knowledge write by Leopoldo Bertossi. This book was released on 2023-04-27. Reasoning Web. Causality, Explanations and Declarative Knowledge available in PDF, EPUB and Kindle. 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.
Combining Soft Computing and Statistical Methods in Data Analysis
Combining Soft Computing and Statistical Methods in Data Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Combining Soft Computing and Statistical Methods in Data Analysis write by Christian Borgelt. This book was released on 2010-10-12. Combining Soft Computing and Statistical Methods in Data Analysis available in PDF, EPUB and Kindle. Over the last forty years there has been a growing interest to extend probability theory and statistics and to allow for more flexible modelling of imprecision, uncertainty, vagueness and ignorance. The fact that in many real-life situations data uncertainty is not only present in the form of randomness (stochastic uncertainty) but also in the form of imprecision/fuzziness is but one point underlining the need for a widening of statistical tools. Most such extensions originate in a "softening" of classical methods, allowing, in particular, to work with imprecise or vague data, considering imprecise or generalized probabilities and fuzzy events, etc. About ten years ago the idea of establishing a recurrent forum for discussing new trends in the before-mentioned context was born and resulted in the first International Conference on Soft Methods in Probability and Statistics (SMPS) that was held in Warsaw in 2002. In the following years the conference took place in Oviedo (2004), in Bristol (2006) and in Toulouse (2008). In the current edition the conference returns to Oviedo. This edited volume is a collection of papers presented at the SMPS 2010 conference held in Mieres and Oviedo. It gives a comprehensive overview of current research into the fusion of soft methods with probability and statistics.
