Information and Complexity in Statistical Modeling
Information and Complexity in Statistical Modeling

Author: Jorma Rissanen

Publisher: Springer Science & Business Media

Published: 2007-12-15

Total Pages: 145

ISBN-13: 0387688129

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No statistical model is "true" or "false," "right" or "wrong"; the models just have varying performance, which can be assessed. The main theme in this book is to teach modeling based on the principle that the objective is to extract the information from data that can be learned with suggested classes of probability models. The intuitive and fundamental concepts of complexity, learnable information, and noise are formalized, which provides a firm information theoretic foundation for statistical modeling. Although the prerequisites include only basic probability calculus and statistics, a moderate level of mathematical proficiency would be beneficial.

Information And Complexity
Information And Complexity

Author: Mark Burgin

Publisher: World Scientific

Published: 2016-11-28

Total Pages: 410

ISBN-13: 9813109041

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The book is a collection of papers of experts in the fields of information and complexity. Information is a basic structure of the world, while complexity is a fundamental property of systems and processes. There are intrinsic relations between information and complexity.The research in information theory, the theory of complexity and their interrelations is very active. The book will expand knowledge on information, complexity and their relations representing the most recent and advanced studies and achievements in this area.The goal of the book is to present the topic from different perspectives — mathematical, informational, philosophical, methodological, etc.

Information-based Complexity
Information-based Complexity

Author: Joseph Frederick Traub

Publisher:

Published: 1988

Total Pages: 552

ISBN-13:

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This book provides a comprehensive treatment of information-based complexity, the branch of computational complexity that deals with the intrinsic difficulty of the approximate solution of problems for which the information is partial, noisy, and priced. Such problems arise in many areas including economics, physics, human and robotic vision, scientific and engineering computation, geophysics, decision theory, signal processing and control theory.

Complexity and Information
Complexity and Information

Author: J. F. Traub

Publisher: Cambridge University Press

Published: 1998-12-10

Total Pages: 152

ISBN-13: 9780521485067

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The twin themes of computational complexity and information pervade this 1998 book. It starts with an introduction to the computational complexity of continuous mathematical models, that is, information-based complexity. This is then used to illustrate a variety of topics, including breaking the curse of dimensionality, complexity of path integration, solvability of ill-posed problems, the value of information in computation, assigning values to mathematical hypotheses, and new, improved methods for mathematical finance. The style is informal, and the goals are exposition, insight and motivation. A comprehensive bibliography is provided, to which readers are referred for precise statements of results and their proofs. As the first introductory book on the subject it will be invaluable as a guide to the area for the many students and researchers whose disciplines, ranging from physics to finance, are influenced by the computational complexity of continuous problems.

Dynamics, Information and Complexity in Quantum Systems
Dynamics, Information and Complexity in Quantum Systems

Author: Fabio Benatti

Publisher: Springer Science & Business Media

Published: 2009-04-17

Total Pages: 535

ISBN-13: 1402093063

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This book offers a self-contained overview of the entropic approach to quantum dynamical systems. In it, complexity in quantum dynamics is addressed by comparison with the classical ergodic, information, and algorithmic complexity theories.

An Introduction to Kolmogorov Complexity and Its Applications
An Introduction to Kolmogorov Complexity and Its Applications

Author: Ming Li

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 655

ISBN-13: 1475726066

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Briefly, we review the basic elements of computability theory and prob ability theory that are required. Finally, in order to place the subject in the appropriate historical and conceptual context we trace the main roots of Kolmogorov complexity. This way the stage is set for Chapters 2 and 3, where we introduce the notion of optimal effective descriptions of objects. The length of such a description (or the number of bits of information in it) is its Kolmogorov complexity. We treat all aspects of the elementary mathematical theory of Kolmogorov complexity. This body of knowledge may be called algo rithmic complexity theory. The theory of Martin-Lof tests for random ness of finite objects and infinite sequences is inextricably intertwined with the theory of Kolmogorov complexity and is completely treated. We also investigate the statistical properties of finite strings with high Kolmogorov complexity. Both of these topics are eminently useful in the applications part of the book. We also investigate the recursion theoretic properties of Kolmogorov complexity (relations with Godel's incompleteness result), and the Kolmogorov complexity version of infor mation theory, which we may call "algorithmic information theory" or "absolute information theory. " The treatment of algorithmic probability theory in Chapter 4 presup poses Sections 1. 6, 1. 11. 2, and Chapter 3 (at least Sections 3. 1 through 3. 4).

Data Complexity in Pattern Recognition
Data Complexity in Pattern Recognition

Author: Mitra Basu

Publisher: Springer Science & Business Media

Published: 2006-12-22

Total Pages: 309

ISBN-13: 1846281725

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Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.

Computational Complexity
Computational Complexity

Author: Sanjeev Arora

Publisher: Cambridge University Press

Published: 2009-04-20

Total Pages: 609

ISBN-13: 0521424267

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New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students.

Complexity, Entropy And The Physics Of Information
Complexity, Entropy And The Physics Of Information

Author: Wojciech H. Zurek

Publisher: CRC Press

Published: 2018-03-08

Total Pages: 545

ISBN-13: 0429971435

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This book has emerged from a meeting held during the week of May 29 to June 2, 1989, at St. John’s College in Santa Fe under the auspices of the Santa Fe Institute. The (approximately 40) official participants as well as equally numerous “groupies” were enticed to Santa Fe by the above “manifesto.” The book—like the “Complexity, Entropy and the Physics of Information” meeting explores not only the connections between quantum and classical physics, information and its transfer, computation, and their significance for the formulation of physical theories, but it also considers the origins and evolution of the information-processing entities, their complexity, and the manner in which they analyze their perceptions to form models of the Universe. As a result, the contributions can be divided into distinct sections only with some difficulty. Indeed, I regard this degree of overlapping as a measure of the success of the meeting. It signifies consensus about the important questions and on the anticipated answers: they presumably lie somewhere in the “border territory,” where information, physics, complexity, quantum, and computation all meet.

Visual Complexity
Visual Complexity

Author: Manuel Lima

Publisher: Princeton Architectural Press

Published: 2013-09-10

Total Pages: 272

ISBN-13: 9781616892197

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Manuel Lima's smash hit Visual Complexity is now available in paperback. This groundbreaking 2011 book—the first to combine a thorough history of information visualization with a detailed look at today's most innovative applications—clearly illustrates why making meaningful connections inside complex data networks has emerged as one of the biggest challenges in twenty-first-century design. From diagramming networks of friends on Facebook to depicting interactions among proteins in a human cell, Visual Complexity presents one hundred of the most interesting examples of informationvisualization by the field's leading practitioners.