Theoretical Computer Science

Theoretical Computer Science PDF Author: Juraj Hromkovič
Publisher: Springer Science & Business Media
ISBN: 9783540140153
Category : Computers
Languages : en
Pages : 336

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Book Description
Juraj Hromkovic takes the reader on an elegant route through the theoretical fundamentals of computer science. The author shows that theoretical computer science is a fascinating discipline, full of spectacular contributions and miracles. The book also presents the development of the computer scientist's way of thinking as well as fundamental concepts such as approximation and randomization in algorithmics, and the basic ideas of cryptography and interconnection network design.

Theoretical Computer Science

Theoretical Computer Science PDF Author: Juraj Hromkovič
Publisher: Springer Science & Business Media
ISBN: 9783540140153
Category : Computers
Languages : en
Pages : 336

Get Book Here

Book Description
Juraj Hromkovic takes the reader on an elegant route through the theoretical fundamentals of computer science. The author shows that theoretical computer science is a fascinating discipline, full of spectacular contributions and miracles. The book also presents the development of the computer scientist's way of thinking as well as fundamental concepts such as approximation and randomization in algorithmics, and the basic ideas of cryptography and interconnection network design.

Gems of Theoretical Computer Science

Gems of Theoretical Computer Science PDF Author: Uwe Schöning
Publisher: Springer Science & Business Media
ISBN: 364260322X
Category : Computers
Languages : en
Pages : 318

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Book Description
This book assembles some of the most important problems and solutions in theoretical computer science-from computability, logic, circuit theory, and complexity. The book presents these important results with complete proofs in an understandable form. It also presents previously open problems that have found (perhaps unexpected) solutions, and challenges the reader to pursue further active research in computer science.

Introduction to Circuit Complexity

Introduction to Circuit Complexity PDF Author: Heribert Vollmer
Publisher: Springer Science & Business Media
ISBN: 3662039273
Category : Computers
Languages : en
Pages : 277

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Book Description
An advanced textbook giving a broad, modern view of the computational complexity theory of boolean circuits, with extensive references, for theoretical computer scientists and mathematicians.

Computable Analysis

Computable Analysis PDF Author: Klaus Weihrauch
Publisher: Springer Science & Business Media
ISBN: 9783540668176
Category : Computers
Languages : en
Pages : 312

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Book Description
Merging fundamental concepts of analysis and recursion theory to a new exciting theory, this book provides a solid fundament for studying various aspects of computability and complexity in analysis. It is the result of an introductory course given for several years and is written in a style suitable for graduate-level and senior students in computer science and mathematics. Many examples illustrate the new concepts while numerous exercises of varying difficulty extend the material and stimulate readers to work actively on the text.

Computational Complexity

Computational Complexity PDF Author: Christos H. Papadimitriou
Publisher: MacMillan Publishing Company
ISBN: 9780020153085
Category : Computational complexity
Languages : en
Pages : 523

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Book Description
The first unified introduction and reference for the field of computational complexity. Virtually non-existent only 25 years ago, computational complexity has expanded tremendously and now comprises a major part of the researh activity in theoretical science.

The Nature of Computation

The Nature of Computation PDF Author: Cristopher Moore
Publisher: OUP Oxford
ISBN: 0191620807
Category : Science
Languages : en
Pages : 1498

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Book Description
Computational complexity is one of the most beautiful fields of modern mathematics, and it is increasingly relevant to other sciences ranging from physics to biology. But this beauty is often buried underneath layers of unnecessary formalism, and exciting recent results like interactive proofs, phase transitions, and quantum computing are usually considered too advanced for the typical student. This book bridges these gaps by explaining the deep ideas of theoretical computer science in a clear and enjoyable fashion, making them accessible to non-computer scientists and to computer scientists who finally want to appreciate their field from a new point of view. The authors start with a lucid and playful explanation of the P vs. NP problem, explaining why it is so fundamental, and so hard to resolve. They then lead the reader through the complexity of mazes and games; optimization in theory and practice; randomized algorithms, interactive proofs, and pseudorandomness; Markov chains and phase transitions; and the outer reaches of quantum computing. At every turn, they use a minimum of formalism, providing explanations that are both deep and accessible. The book is intended for graduate and undergraduate students, scientists from other areas who have long wanted to understand this subject, and experts who want to fall in love with this field all over again.

Algorithms and Complexity

Algorithms and Complexity PDF Author: Bozzano G Luisa
Publisher: Elsevier
ISBN: 9780444880710
Category : Computers
Languages : en
Pages : 1014

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Book Description
This first part presents chapters on models of computation, complexity theory, data structures, and efficient computation in many recognized sub-disciplines of Theoretical Computer Science.

Introduction to the Theory of Computation

Introduction to the Theory of Computation PDF Author: Michael Sipser
Publisher: Cengage Learning
ISBN: 9781133187790
Category : Computers
Languages : en
Pages : 0

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Book Description
Now you can clearly present even the most complex computational theory topics to your students with Sipser’s distinct, market-leading INTRODUCTION TO THE THEORY OF COMPUTATION, 3E. The number one choice for today’s computational theory course, this highly anticipated revision retains the unmatched clarity and thorough coverage that make it a leading text for upper-level undergraduate and introductory graduate students. This edition continues author Michael Sipser’s well-known, approachable style with timely revisions, additional exercises, and more memorable examples in key areas. A new first-of-its-kind theoretical treatment of deterministic context-free languages is ideal for a better understanding of parsing and LR(k) grammars. This edition’s refined presentation ensures a trusted accuracy and clarity that make the challenging study of computational theory accessible and intuitive to students while maintaining the subject’s rigor and formalism. Readers gain a solid understanding of the fundamental mathematical properties of computer hardware, software, and applications with a blend of practical and philosophical coverage and mathematical treatments, including advanced theorems and proofs. INTRODUCTION TO THE THEORY OF COMPUTATION, 3E’s comprehensive coverage makes this an ideal ongoing reference tool for those studying theoretical computing. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

An Introduction to Computational Learning Theory

An Introduction to Computational Learning Theory PDF Author: Michael J. Kearns
Publisher: MIT Press
ISBN: 9780262111935
Category : Computers
Languages : en
Pages : 230

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Book Description
Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.

The Usefulness of Useless Knowledge

The Usefulness of Useless Knowledge PDF Author: Abraham Flexner
Publisher: Princeton University Press
ISBN: 0691174768
Category : Reference
Languages : en
Pages : 104

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Book Description
A short, provocative book about why "useless" science often leads to humanity's greatest technological breakthroughs A forty-year tightening of funding for scientific research has meant that resources are increasingly directed toward applied or practical outcomes, with the intent of creating products of immediate value. In such a scenario, it makes sense to focus on the most identifiable and urgent problems, right? Actually, it doesn't. In his classic essay "The Usefulness of Useless Knowledge," Abraham Flexner, the founding director of the Institute for Advanced Study in Princeton and the man who helped bring Albert Einstein to the United States, describes a great paradox of scientific research. The search for answers to deep questions, motivated solely by curiosity and without concern for applications, often leads not only to the greatest scientific discoveries but also to the most revolutionary technological breakthroughs. In short, no quantum mechanics, no computer chips. This brief book includes Flexner's timeless 1939 essay alongside a new companion essay by Robbert Dijkgraaf, the Institute's current director, in which he shows that Flexner's defense of the value of "the unobstructed pursuit of useless knowledge" may be even more relevant today than it was in the early twentieth century. Dijkgraaf describes how basic research has led to major transformations in the past century and explains why it is an essential precondition of innovation and the first step in social and cultural change. He makes the case that society can achieve deeper understanding and practical progress today and tomorrow only by truly valuing and substantially funding the curiosity-driven "pursuit of useless knowledge" in both the sciences and the humanities.