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Author: Luis A. García-Escudero
Publisher: Springer Nature
ISBN: 3031155092
Category : Computers
Languages : en
Pages : 421
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Book Description
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.
Author: Luis A. García-Escudero
Publisher: Springer Nature
ISBN: 3031155092
Category : Computers
Languages : en
Pages : 421
Get Book Here
Book Description
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.
Author: Luis A. García-Escudero
Publisher:
ISBN: 9783031155109
Category :
Languages : en
Pages : 0
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Book Description
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.
Author: Sven Knoth
Publisher: Springer Nature
ISBN: 3031691113
Category :
Languages : en
Pages : 503
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Book Description
Author: Jonathan Ansari
Publisher: Springer Nature
ISBN: 3031659937
Category :
Languages : en
Pages : 579
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Book Description
Author: Leopoldo Bertossi
Publisher: Springer Nature
ISBN: 303131414X
Category : Computers
Languages : en
Pages : 219
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Book Description
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.
Author: Göran Kauermann
Publisher: Springer Nature
ISBN: 3030698270
Category : Mathematics
Languages : en
Pages : 361
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Book Description
This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty. Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design. The textbook includes sufficient material for a two-semester course and is intended for master’s students in data science, statistics and computer science with a rudimentary grasp of probability theory. It will also be useful for data science practitioners who want to strengthen their statistics skills.
Author: Christian Bird
Publisher: Elsevier
ISBN: 0124115438
Category : Computers
Languages : en
Pages : 673
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Book Description
The Art and Science of Analyzing Software Data provides valuable information on analysis techniques often used to derive insight from software data. This book shares best practices in the field generated by leading data scientists, collected from their experience training software engineering students and practitioners to master data science. The book covers topics such as the analysis of security data, code reviews, app stores, log files, and user telemetry, among others. It covers a wide variety of techniques such as co-change analysis, text analysis, topic analysis, and concept analysis, as well as advanced topics such as release planning and generation of source code comments. It includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source, present results to stakeholders, and drive decisions. - Presents best practices, hints, and tips to analyze data and apply tools in data science projects - Presents research methods and case studies that have emerged over the past few years to further understanding of software data - Shares stories from the trenches of successful data science initiatives in industry
Author: Jianqing Fan
Publisher: CRC Press
ISBN: 0429527616
Category : Mathematics
Languages : en
Pages : 974
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Book Description
Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
Author: R. Röhrig
Publisher: IOS Press
ISBN: 1614998086
Category : Medical
Languages : en
Pages : 244
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Book Description
We live in an age characterized by computerized information, but ubiquitous information technology has profoundly changed our healthcare systems and, if not adequately trained to deal with it, healthcare professionals can all too easily be overwhelmed by the complexity and magnitude of the data. This demands new skills from physicians as well as novel ways to provide medical knowledge. Selecting and assessing relevant information presents a challenge which can only be met by bridging the various disciplines in healthcare and the data sciences. This book presents the proceedings of the 62nd annual meeting of the German Association of Medical Informatics, Biometry and Epidemiology (German Medical Data Sciences – GMDS 2017): Visions and Bridges, held in Oldenburg, Germany, in September 2017. The 242 submissions to the conference included 77 full papers, of which 42 were accepted for publication here after rigorous review. These are divided into 7 sections: teaching and training; epidemiological surveillance, screening and registration; research methods; IT infrastructure for biomedical research/data integration centers; healthcare information systems; interoperability – standards, terminologies, classification; and biomedical informatics, innovative algorithms and signal processing. The book provides a vision for healthcare in the information age, and will be of interest to all those concerned with improving clinical decision making and the effectiveness and efficiency of health systems using data methods and technology.
Author: Georg Rehm
Publisher: Springer Science & Business Media
ISBN: 364230558X
Category : Computers
Languages : en
Pages : 90
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Book Description
This white paper is part of a series that promotes knowledge about language technology and its potential. It addresses educators, journalists, politicians, language communities and others. The availability and use of language technology in Europe varies between languages. Consequently, the actions that are required to further support research and development of language technologies also differ for each language. The required actions depend on many factors, such as the complexity of a given language and the size of its community. META-NET, a Network of Excellence funded by the European Commission, has conducted an analysis of current language resources and technologies. This analysis focused on the 23 official European languages as well as other important national and regional languages in Europe. The results of this analysis suggest that there are many significant research gaps for each language. A more detailed expert analysis and assessment of the current situation will help maximise the impact of additional research and minimize any risks. META-NET consists of 54 research centres from 33 countries that are working with stakeholders from commercial businesses, government agencies, industry, research organisations, software companies, technology providers and European universities. Together, they are creating a common technology vision while developing a strategic research agenda that shows how language technology applications can address any research gaps by 2020.
