Information Theory Meets Power Laws

Information Theory Meets Power Laws PDF

Author: Lukasz Debowski

Publisher: John Wiley & Sons

Published: 2020-12-10

Total Pages: 384

ISBN-13: 1119625270

DOWNLOAD EBOOK →

Discover new theoretical connections between stochastic phenomena and the structure of natural language with this powerful volume! Information Theory Meets Power Laws: Stochastic Processes and Language Models presents readers with a novel subtype of a probabilistic approach to language, which is based on statistical laws of texts and their analysis by means of information theory. The distinguished author insightfully and rigorously examines the linguistic and mathematical subject matter while eschewing needlessly abstract and superfluous constructions. The book begins with a less formal treatment of its subjects in the first chapter, introducing its concepts to readers without mathematical training and allowing those unfamiliar with linguistics to learn the book’s motivations. Despite its inherent complexity, Information Theory Meets Power Laws: Stochastic Processes and Language Models is a surprisingly approachable treatment of idealized mathematical models of human language. The author succeeds in developing some of the theory underlying fundamental stochastic and semantic phenomena, like strong nonergodicity, in a way that has not previously been seriously attempted. In doing so, he covers topics including: Zipf’s and Herdan’s laws for natural language Power laws for information, repetitions, and correlations Markov, finite-state,and Santa Fe processes Bayesian and frequentist interpretations of probability Ergodic decomposition, Kolmogorov complexity, and universal coding Theorems about facts and words Information measures for fields Rényi entropies, recurrence times, and subword complexity Asymptotically mean stationary processes Written primarily for mathematics graduate students and professionals interested in information theory or discrete stochastic processes, Information Theory Meets Power Laws: Stochastic Processes and Language Models also belongs on the bookshelves of doctoral students and researchers in artificial intelligence, computational and quantitative linguistics as well as physics of complex systems.

Information Theory Meets Power Laws

Information Theory Meets Power Laws PDF

Author: Lukasz Debowski

Publisher: John Wiley & Sons

Published: 2020-12-10

Total Pages: 384

ISBN-13: 1119625270

DOWNLOAD EBOOK →

Discover new theoretical connections between stochastic phenomena and the structure of natural language with this powerful volume! Information Theory Meets Power Laws: Stochastic Processes and Language Models presents readers with a novel subtype of a probabilistic approach to language, which is based on statistical laws of texts and their analysis by means of information theory. The distinguished author insightfully and rigorously examines the linguistic and mathematical subject matter while eschewing needlessly abstract and superfluous constructions. The book begins with a less formal treatment of its subjects in the first chapter, introducing its concepts to readers without mathematical training and allowing those unfamiliar with linguistics to learn the book’s motivations. Despite its inherent complexity, Information Theory Meets Power Laws: Stochastic Processes and Language Models is a surprisingly approachable treatment of idealized mathematical models of human language. The author succeeds in developing some of the theory underlying fundamental stochastic and semantic phenomena, like strong nonergodicity, in a way that has not previously been seriously attempted. In doing so, he covers topics including: Zipf’s and Herdan’s laws for natural language Power laws for information, repetitions, and correlations Markov, finite-state,and Santa Fe processes Bayesian and frequentist interpretations of probability Ergodic decomposition, Kolmogorov complexity, and universal coding Theorems about facts and words Information measures for fields Rényi entropies, recurrence times, and subword complexity Asymptotically mean stationary processes Written primarily for mathematics graduate students and professionals interested in information theory or discrete stochastic processes, Information Theory Meets Power Laws: Stochastic Processes and Language Models also belongs on the bookshelves of doctoral students and researchers in artificial intelligence, computational and quantitative linguistics as well as physics of complex systems.

Information Theory Meets Power Laws

Information Theory Meets Power Laws PDF

Author: Lukasz Debowski

Publisher: John Wiley & Sons

Published: 2020-12-01

Total Pages: 384

ISBN-13: 1119625378

DOWNLOAD EBOOK →

Discover new theoretical connections between stochastic phenomena and the structure of natural language with this powerful volume! Information Theory Meets Power Laws: Stochastic Processes and Language Models presents readers with a novel subtype of a probabilistic approach to language, which is based on statistical laws of texts and their analysis by means of information theory. The distinguished author insightfully and rigorously examines the linguistic and mathematical subject matter while eschewing needlessly abstract and superfluous constructions. The book begins with a less formal treatment of its subjects in the first chapter, introducing its concepts to readers without mathematical training and allowing those unfamiliar with linguistics to learn the book’s motivations. Despite its inherent complexity, Information Theory Meets Power Laws: Stochastic Processes and Language Models is a surprisingly approachable treatment of idealized mathematical models of human language. The author succeeds in developing some of the theory underlying fundamental stochastic and semantic phenomena, like strong nonergodicity, in a way that has not previously been seriously attempted. In doing so, he covers topics including: Zipf’s and Herdan’s laws for natural language Power laws for information, repetitions, and correlations Markov, finite-state,and Santa Fe processes Bayesian and frequentist interpretations of probability Ergodic decomposition, Kolmogorov complexity, and universal coding Theorems about facts and words Information measures for fields Rényi entropies, recurrence times, and subword complexity Asymptotically mean stationary processes Written primarily for mathematics graduate students and professionals interested in information theory or discrete stochastic processes, Information Theory Meets Power Laws: Stochastic Processes and Language Models also belongs on the bookshelves of doctoral students and researchers in artificial intelligence, computational and quantitative linguistics as well as physics of complex systems.

Knowledge and Power

Knowledge and Power PDF

Author: George Gilder

Publisher: Regnery Publishing

Published: 2013-06-10

Total Pages: 370

ISBN-13: 1621570274

DOWNLOAD EBOOK →

Ronald Reagan’s most-quoted living author—George Gilder—is back with an all-new paradigm-shifting theory of capitalism that will upturn conventional wisdom, just when our economy desperately needs a new direction. America’s struggling economy needs a better philosophy than the college student's lament: "I can't be out of money, I still have checks in my checkbook!" We’ve tried a government spending spree, and we’ve learned it doesn’t work. Now is the time to rededicate our country to the pursuit of free market capitalism, before we’re buried under a mound of debt and unfunded entitlements. But how do we navigate between government spending that's too big to sustain and financial institutions that are "too big to fail?" In Knowledge and Power, George Gilder proposes a bold new theory on how capitalism produces wealth and how our economy can regain its vitality and its growth. Gilder breaks away from the supply-side model of economics to present a new economic paradigm: the epic conflict between the knowledge of entrepreneurs on one side, and the blunt power of government on the other. The knowledge of entrepreneurs, and their freedom to share and use that knowledge, are the sparks that light up the economy and set its gears in motion. The power of government to regulate, stifle, manipulate, subsidize or suppress knowledge and ideas is the inertia that slows those gears down, or keeps them from turning at all. One of the twentieth century’s defining economic minds has returned with a new philosophy to carry us into the twenty-first. Knowledge and Power is a must-read for fiscal conservatives, business owners, CEOs, investors, and anyone interested in propelling America’s economy to future success.

Information Theory and Language

Information Theory and Language PDF

Author: Łukasz Dębowski

Publisher: MDPI

Published: 2020-12-15

Total Pages: 244

ISBN-13: 3039360264

DOWNLOAD EBOOK →

“Information Theory and Language” is a collection of 12 articles that appeared recently in Entropy as part of a Special Issue of the same title. These contributions represent state-of-the-art interdisciplinary research at the interface of information theory and language studies. They concern in particular: • Applications of information theoretic concepts such as Shannon and Rényi entropies, mutual information, and rate–distortion curves to the research of natural languages; • Mathematical work in information theory inspired by natural language phenomena, such as deriving moments of subword complexity or proving continuity of mutual information; • Empirical and theoretical investigation of quantitative laws of natural language such as Zipf’s law, Herdan’s law, and Menzerath–Altmann’s law; • Empirical and theoretical investigations of statistical language models, including recently developed neural language models, their entropies, and other parameters; • Standardizing language resources for statistical investigation of natural language; • Other topics concerning semantics, syntax, and critical phenomena. Whereas the traditional divide between probabilistic and formal approaches to human language, cultivated in the disjoint scholarships of natural sciences and humanities, has been blurred in recent years, this book can contribute to pointing out potential areas of future research cross-fertilization.

Elements of Information Theory

Elements of Information Theory PDF

Author: Thomas M. Cover

Publisher: John Wiley & Sons

Published: 2012-11-28

Total Pages: 788

ISBN-13: 1118585771

DOWNLOAD EBOOK →

The latest edition of this classic is updated with new problem sets and material The Second Edition of this fundamental textbook maintains the book's tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory. All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points. The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated references Now current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.

Information Theory and the Central Limit Theorem

Information Theory and the Central Limit Theorem PDF

Author: Oliver Thomas Johnson

Publisher: World Scientific

Published: 2004

Total Pages: 224

ISBN-13: 1860944736

DOWNLOAD EBOOK →

This book provides a comprehensive description of a new method of proving the central limit theorem, through the use of apparently unrelated results from information theory. It gives a basic introduction to the concepts of entropy and Fisher information, and collects together standard results concerning their behaviour. It brings together results from a number of research papers as well as unpublished material, showing how the techniques can give a unified view of limit theorems.

The Mathematical Theory of Communication

The Mathematical Theory of Communication PDF

Author: Claude E Shannon

Publisher: University of Illinois Press

Published: 1998-09-01

Total Pages: 144

ISBN-13: 025209803X

DOWNLOAD EBOOK →

Scientific knowledge grows at a phenomenal pace--but few books have had as lasting an impact or played as important a role in our modern world as The Mathematical Theory of Communication, published originally as a paper on communication theory more than fifty years ago. Republished in book form shortly thereafter, it has since gone through four hardcover and sixteen paperback printings. It is a revolutionary work, astounding in its foresight and contemporaneity. The University of Illinois Press is pleased and honored to issue this commemorative reprinting of a classic.

Network Information Theory

Network Information Theory PDF

Author: Abbas El Gamal

Publisher: Cambridge University Press

Published: 2011-12-08

Total Pages: 666

ISBN-13: 1139503146

DOWNLOAD EBOOK →

This comprehensive treatment of network information theory and its applications provides the first unified coverage of both classical and recent results. With an approach that balances the introduction of new models and new coding techniques, readers are guided through Shannon's point-to-point information theory, single-hop networks, multihop networks, and extensions to distributed computing, secrecy, wireless communication, and networking. Elementary mathematical tools and techniques are used throughout, requiring only basic knowledge of probability, whilst unified proofs of coding theorems are based on a few simple lemmas, making the text accessible to newcomers. Key topics covered include successive cancellation and superposition coding, MIMO wireless communication, network coding, and cooperative relaying. Also covered are feedback and interactive communication, capacity approximations and scaling laws, and asynchronous and random access channels. This book is ideal for use in the classroom, for self-study, and as a reference for researchers and engineers in industry and academia.

Power Laws in Economics and Finance

Power Laws in Economics and Finance PDF

Author: Xavier Gabaix

Publisher:

Published: 2008

Total Pages: 78

ISBN-13:

DOWNLOAD EBOOK →

A power law is the form taken by a large number of surprising empirical regularities in economics and finance. This article surveys well-documented empirical power laws concerning income and wealth, the size of cities and firms, stock market returns, trading volume, international trade, and executive pay. It reviews detail-independent theoretical motivations that make sharp predictions concerning the existence and coefficients of power laws, without requiring delicate tuning of model parameters. These theoretical mechanisms include random growth, optimization, and the economics of superstars coupled with extreme value theory. Some of the empirical regularities currently lack an appropriate explanation. This article highlights these open areas for future research.