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Information-Theoretic Methods in Data Science

Information-Theoretic Methods in Data Science PDF Author: Miguel R. D. Rodrigues
Publisher: Cambridge University Press
ISBN: 1108427138
Category : Computers
Languages : en
Pages : 561

Book Description
The first unified treatment of the interface between information theory and emerging topics in data science, written in a clear, tutorial style. Covering topics such as data acquisition, representation, analysis, and communication, it is ideal for graduate students and researchers in information theory, signal processing, and machine learning.

Information-Theoretic Methods in Data Science

Information-Theoretic Methods in Data Science PDF Author: Miguel R. D. Rodrigues
Publisher: Cambridge University Press
ISBN: 1108427138
Category : Computers
Languages : en
Pages : 561

Book Description
The first unified treatment of the interface between information theory and emerging topics in data science, written in a clear, tutorial style. Covering topics such as data acquisition, representation, analysis, and communication, it is ideal for graduate students and researchers in information theory, signal processing, and machine learning.

Information Theory and Statistical Learning

Information Theory and Statistical Learning PDF Author: Frank Emmert-Streib
Publisher: Springer Science & Business Media
ISBN: 0387848150
Category : Computers
Languages : en
Pages : 443

Book Description
This interdisciplinary text offers theoretical and practical results of information theoretic methods used in statistical learning. It presents a comprehensive overview of the many different methods that have been developed in numerous contexts.

Information Theory, Inference and Learning Algorithms

Information Theory, Inference and Learning Algorithms PDF Author: David J. C. MacKay
Publisher: Cambridge University Press
ISBN: 9780521642989
Category : Computers
Languages : en
Pages : 694

Book Description
Table of contents

Model Selection and Multimodel Inference

Model Selection and Multimodel Inference PDF Author: Kenneth P. Burnham
Publisher: Springer Science & Business Media
ISBN: 0387224564
Category : Mathematics
Languages : en
Pages : 488

Book Description
A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.

Information Theory and Statistics

Information Theory and Statistics PDF Author: Solomon Kullback
Publisher: Courier Corporation
ISBN: 0486142043
Category : Mathematics
Languages : en
Pages : 460

Book Description
Highly useful text studies logarithmic measures of information and their application to testing statistical hypotheses. Includes numerous worked examples and problems. References. Glossary. Appendix. 1968 2nd, revised edition.

Statistical Inference for Engineers and Data Scientists

Statistical Inference for Engineers and Data Scientists PDF Author: Pierre Moulin
Publisher: Cambridge University Press
ISBN: 1107185920
Category : Mathematics
Languages : en
Pages : 423

Book Description
A mathematically accessible textbook introducing all the tools needed to address modern inference problems in engineering and data science.

Towards an Information Theory of Complex Networks

Towards an Information Theory of Complex Networks PDF Author: Matthias Dehmer
Publisher: Springer Science & Business Media
ISBN: 0817649042
Category : Mathematics
Languages : en
Pages : 409

Book Description
For over a decade, complex networks have steadily grown as an important tool across a broad array of academic disciplines, with applications ranging from physics to social media. A tightly organized collection of carefully-selected papers on the subject, Towards an Information Theory of Complex Networks: Statistical Methods and Applications presents theoretical and practical results about information-theoretic and statistical models of complex networks in the natural sciences and humanities. The book's major goal is to advocate and promote a combination of graph-theoretic, information-theoretic, and statistical methods as a way to better understand and characterize real-world networks. This volume is the first to present a self-contained, comprehensive overview of information-theoretic models of complex networks with an emphasis on applications. As such, it marks a first step toward establishing advanced statistical information theory as a unified theoretical basis of complex networks for all scientific disciplines and can serve as a valuable resource for a diverse audience of advanced students and professional scientists. While it is primarily intended as a reference for research, the book could also be a useful supplemental graduate text in courses related to information science, graph theory, machine learning, and computational biology, among others.

Information Theoretic Learning

Information Theoretic Learning PDF Author: Jose C. Principe
Publisher: Springer Science & Business Media
ISBN: 1441915702
Category : Computers
Languages : en
Pages : 538

Book Description
This book is the first cohesive treatment of ITL algorithms to adapt linear or nonlinear learning machines both in supervised and unsupervised paradigms. It compares the performance of ITL algorithms with the second order counterparts in many applications.

Graph Theoretic Methods in Multiagent Networks

Graph Theoretic Methods in Multiagent Networks PDF Author: Mehran Mesbahi
Publisher: Princeton University Press
ISBN: 1400835356
Category : Mathematics
Languages : en
Pages : 424

Book Description
This accessible book provides an introduction to the analysis and design of dynamic multiagent networks. Such networks are of great interest in a wide range of areas in science and engineering, including: mobile sensor networks, distributed robotics such as formation flying and swarming, quantum networks, networked economics, biological synchronization, and social networks. Focusing on graph theoretic methods for the analysis and synthesis of dynamic multiagent networks, the book presents a powerful new formalism and set of tools for networked systems. The book's three sections look at foundations, multiagent networks, and networks as systems. The authors give an overview of important ideas from graph theory, followed by a detailed account of the agreement protocol and its various extensions, including the behavior of the protocol over undirected, directed, switching, and random networks. They cover topics such as formation control, coverage, distributed estimation, social networks, and games over networks. And they explore intriguing aspects of viewing networks as systems, by making these networks amenable to control-theoretic analysis and automatic synthesis, by monitoring their dynamic evolution, and by examining higher-order interaction models in terms of simplicial complexes and their applications. The book will interest graduate students working in systems and control, as well as in computer science and robotics. It will be a standard reference for researchers seeking a self-contained account of system-theoretic aspects of multiagent networks and their wide-ranging applications. This book has been adopted as a textbook at the following universities: ? University of Stuttgart, Germany Royal Institute of Technology, Sweden Johannes Kepler University, Austria Georgia Tech, USA University of Washington, USA Ohio University, USA

Information Theoretic Perspectives on 5G Systems and Beyond

Information Theoretic Perspectives on 5G Systems and Beyond PDF Author: Ivana Marić
Publisher:
ISBN: 1108271367
Category : Language Arts & Disciplines
Languages : en
Pages : 768

Book Description
Understand key information-theoretic principles that underpin the design of next-generation cellular systems with this invaluable resource. This book is the perfect tool for researchers and graduate students in the field of information theory and wireless communications, as well as for practitioners in the telecommunications industry.