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| Author | : Gordana Dodig Crnkovic |
| Publisher | : World Scientific |
| Total Pages | : 530 |
| Release | : 2011 |
| Genre | : Computers |
| ISBN | : 9814295477 |
This volume provides a cutting-edge view of the world's leading authorities in fields where information and computation play a central role.
| Author | : Philip Tetlow |
| Publisher | : CRC Press |
| Total Pages | : 407 |
| Release | : 2016-02-24 |
| Genre | : Business & Economics |
| ISBN | : 1317004841 |
The World Wide Web is truly astounding. It has changed the way we interact, learn and innovate. It is the largest sociotechnical system humankind has created and is advancing at a pace that leaves most in awe. It is an unavoidable fact that the future of the world is now inextricably linked to the future of the Web. Almost every day it appears to change, to get better and increase its hold on us. For all this we are starting to see underlying stability emerge. The way that Web sites rank in terms of popularity, for example, appears to follow laws with which we are familiar. What is fascinating is that these laws were first discovered, not in fields like computer science or information technology, but in what we regard as more fundamental disciplines like biology, physics and mathematics. Consequently the Web, although synthetic at its surface, seems to be quite 'natural' deeper down, and one of the driving aims of the new field of Web Science is to discover how far down such ’naturalness’ goes. If the Web is natural to its core, that raises some fundamental questions. It forces us, for example, to ask if the central properties of the Web might be more elemental than the truths we cling to from our understandings of the physical world. In essence, it demands that we question the very nature of information. Understanding Information and Computation is about such questions and one possible route to potentially mind-blowing answers.
| Author | : Tom Stuart |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 389 |
| Release | : 2013-05-15 |
| Genre | : Computers |
| ISBN | : 144933010X |
Finally, you can learn computation theory and programming language design in an engaging, practical way. Understanding Computation explains theoretical computer science in a context you’ll recognize, helping you appreciate why these ideas matter and how they can inform your day-to-day programming. Rather than use mathematical notation or an unfamiliar academic programming language like Haskell or Lisp, this book uses Ruby in a reductionist manner to present formal semantics, automata theory, and functional programming with the lambda calculus. It’s ideal for programmers versed in modern languages, with little or no formal training in computer science. Understand fundamental computing concepts, such as Turing completeness in languages Discover how programs use dynamic semantics to communicate ideas to machines Explore what a computer can do when reduced to its bare essentials Learn how universal Turing machines led to today’s general-purpose computers Perform complex calculations, using simple languages and cellular automata Determine which programming language features are essential for computation Examine how halting and self-referencing make some computing problems unsolvable Analyze programs by using abstract interpretation and type systems
| Author | : John V. Guttag |
| Publisher | : MIT Press |
| Total Pages | : 466 |
| Release | : 2016-08-12 |
| Genre | : Computers |
| ISBN | : 0262529629 |
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
| Author | : Michael A. Nielsen |
| Publisher | : Cambridge University Press |
| Total Pages | : 709 |
| Release | : 2010-12-09 |
| Genre | : Science |
| ISBN | : 1139495488 |
One of the most cited books in physics of all time, Quantum Computation and Quantum Information remains the best textbook in this exciting field of science. This 10th anniversary edition includes an introduction from the authors setting the work in context. This comprehensive textbook describes such remarkable effects as fast quantum algorithms, quantum teleportation, quantum cryptography and quantum error-correction. Quantum mechanics and computer science are introduced before moving on to describe what a quantum computer is, how it can be used to solve problems faster than 'classical' computers and its real-world implementation. It concludes with an in-depth treatment of quantum information. Containing a wealth of figures and exercises, this well-known textbook is ideal for courses on the subject, and will interest beginning graduate students and researchers in physics, computer science, mathematics, and electrical engineering.
| Author | : Avi Wigderson |
| Publisher | : Princeton University Press |
| Total Pages | : 434 |
| Release | : 2019-10-29 |
| Genre | : Computers |
| ISBN | : 0691189137 |
From the winner of the Turing Award and the Abel Prize, an introduction to computational complexity theory, its connections and interactions with mathematics, and its central role in the natural and social sciences, technology, and philosophy Mathematics and Computation provides a broad, conceptual overview of computational complexity theory—the mathematical study of efficient computation. With important practical applications to computer science and industry, computational complexity theory has evolved into a highly interdisciplinary field, with strong links to most mathematical areas and to a growing number of scientific endeavors. Avi Wigderson takes a sweeping survey of complexity theory, emphasizing the field’s insights and challenges. He explains the ideas and motivations leading to key models, notions, and results. In particular, he looks at algorithms and complexity, computations and proofs, randomness and interaction, quantum and arithmetic computation, and cryptography and learning, all as parts of a cohesive whole with numerous cross-influences. Wigderson illustrates the immense breadth of the field, its beauty and richness, and its diverse and growing interactions with other areas of mathematics. He ends with a comprehensive look at the theory of computation, its methodology and aspirations, and the unique and fundamental ways in which it has shaped and will further shape science, technology, and society. For further reading, an extensive bibliography is provided for all topics covered. Mathematics and Computation is useful for undergraduate and graduate students in mathematics, computer science, and related fields, as well as researchers and teachers in these fields. Many parts require little background, and serve as an invitation to newcomers seeking an introduction to the theory of computation. Comprehensive coverage of computational complexity theory, and beyond High-level, intuitive exposition, which brings conceptual clarity to this central and dynamic scientific discipline Historical accounts of the evolution and motivations of central concepts and models A broad view of the theory of computation's influence on science, technology, and society Extensive bibliography
| Author | : David McMahon |
| Publisher | : John Wiley & Sons |
| Total Pages | : 420 |
| Release | : 2007-12-14 |
| Genre | : Technology & Engineering |
| ISBN | : 9780470181362 |
A self-contained treatment of the fundamentals of quantum computing This clear, practical book takes quantum computing out of the realm of theoretical physics and teaches the fundamentals of the field to students and professionals who have not had training in quantum computing or quantum information theory, including computer scientists, programmers, electrical engineers, mathematicians, physics students, and chemists. The author cuts through the conventions of typical jargon-laden physics books and instead presents the material through his unique "how-to" approach and friendly, conversational style. Readers will learn how to carry out calculations with explicit details and will gain a fundamental grasp of: * Quantum mechanics * Quantum computation * Teleportation * Quantum cryptography * Entanglement * Quantum algorithms * Error correction A number of worked examples are included so readers can see how quantum computing is done with their own eyes, while answers to similar end-of-chapter problems are provided for readers to check their own work as they learn to master the information. Ideal for professionals and graduate-level students alike, Quantum Computing Explained delivers the fundamentals of quantum computing readers need to be able to understand current research papers and go on to study more advanced quantum texts.
| Author | : Marc Mézard |
| Publisher | : Oxford University Press |
| Total Pages | : 584 |
| Release | : 2009-01-22 |
| Genre | : Computers |
| ISBN | : 019857083X |
A very active field of research is emerging at the frontier of statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. This book sets up a common language and pool of concepts, accessible to students and researchers from each of these fields.
| Author | : Eleanor G. Rieffel |
| Publisher | : MIT Press |
| Total Pages | : 389 |
| Release | : 2011-03-04 |
| Genre | : Business & Economics |
| ISBN | : 0262015064 |
A thorough exposition of quantum computing and the underlying concepts of quantum physics, with explanations of the relevant mathematics and numerous examples.
| Author | : John MacCormick |
| Publisher | : Princeton University Press |
| Total Pages | : 404 |
| Release | : 2018-05-01 |
| Genre | : Computers |
| ISBN | : 0691170665 |
An accessible and rigorous textbook for introducing undergraduates to computer science theory What Can Be Computed? is a uniquely accessible yet rigorous introduction to the most profound ideas at the heart of computer science. Crafted specifically for undergraduates who are studying the subject for the first time, and requiring minimal prerequisites, the book focuses on the essential fundamentals of computer science theory and features a practical approach that uses real computer programs (Python and Java) and encourages active experimentation. It is also ideal for self-study and reference. The book covers the standard topics in the theory of computation, including Turing machines and finite automata, universal computation, nondeterminism, Turing and Karp reductions, undecidability, time-complexity classes such as P and NP, and NP-completeness, including the Cook-Levin Theorem. But the book also provides a broader view of computer science and its historical development, with discussions of Turing's original 1936 computing machines, the connections between undecidability and Gödel's incompleteness theorem, and Karp's famous set of twenty-one NP-complete problems. Throughout, the book recasts traditional computer science concepts by considering how computer programs are used to solve real problems. Standard theorems are stated and proven with full mathematical rigor, but motivation and understanding are enhanced by considering concrete implementations. The book's examples and other content allow readers to view demonstrations of—and to experiment with—a wide selection of the topics it covers. The result is an ideal text for an introduction to the theory of computation. An accessible and rigorous introduction to the essential fundamentals of computer science theory, written specifically for undergraduates taking introduction to the theory of computation Features a practical, interactive approach using real computer programs (Python in the text, with forthcoming Java alternatives online) to enhance motivation and understanding Gives equal emphasis to computability and complexity Includes special topics that demonstrate the profound nature of key ideas in the theory of computation Lecture slides and Python programs are available at whatcanbecomputed.com
