Computational Complexity Theory

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Author: Steven Rudich,Avi Wigderson

Publisher: American Mathematical Soc.

ISBN: 082182872X

Category: Mathematics

Page: 389

View: 6350

Computational Complexity Theory is the study of how much of a given resource is required to perform the computations that interest us the most. Four decades of fruitful research have produced a rich and subtle theory of the relationship between different resource measures and problems. At the core of the theory are some of the most alluring open problems in mathematics. This book presents three weeks of lectures from the IAS/Park City Mathematics Institute Summer School on computational complexity. The first week gives a general introduction to the field, including descriptions of the basic models, techniques, results and open problems. The second week focuses on lower bounds in concrete models. The final week looks at randomness in computation, with discussions of different notions of pseudorandomness, interactive proof systems and zero knowledge, and probabilistically checkable proofs (PCPs). It is recommended for independent study by graduate students or researchers interested in computational complexity. The volume is recommended for independent study and is suitable for graduate students and researchers interested in computational complexity.

Computational Complexity

A Modern Approach

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Author: Sanjeev Arora,Boaz Barak

Publisher: Cambridge University Press

ISBN: 9781139477369

Category: Computers

Page: N.A

View: 8085

This beginning graduate textbook describes both recent achievements and classical results of computational complexity theory. Requiring essentially no background apart from mathematical maturity, the book can be used as a reference for self-study for anyone interested in complexity, including physicists, mathematicians, and other scientists, as well as a textbook for a variety of courses and seminars. More than 300 exercises are included with a selected hint set. The book starts with a broad introduction to the field and progresses to advanced results. Contents include: definition of Turing machines and basic time and space complexity classes, probabilistic algorithms, interactive proofs, cryptography, quantum computation, lower bounds for concrete computational models (decision trees, communication complexity, constant depth, algebraic and monotone circuits, proof complexity), average-case complexity and hardness amplification, derandomization and pseudorandom constructions, and the PCP theorem.

The Computational Complexity of Machine Learning

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Author: Michael J. Kearns

Publisher: MIT Press

ISBN: 9780262111522

Category: Computers

Page: 165

View: 9183

We also give algorithms for learning powerful concept classes under the uniform distribution, and give equivalences between natural models of efficient learnability. This thesis also includes detailed definitions and motivation for the distribution-free model, a chapter discussing past research in this model and related models, and a short list of important open problems."

Computational Complexity Theory

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Author: Juris Hartmanis

Publisher: American Mathematical Soc.

ISBN: 0821801317

Category: Mathematics

Page: 128

View: 9247

Computational complexity theory is the study of the quantitative laws that govern computing. During the last 25 years, this field has grown into a rich mathematical theory. Currently one of the most active research areas in computer science, complexity theory is of considerable interest to mathematicians as well, since some of the key open problems in this field raise basic questions about the nature of mathematics. Many experts in complexity theory believe that, in coming decades, the strongest influence on the development of mathematics will come from the extended use of computing and from concepts and problems arising in computer science.This volume contains the proceedings of the AMS Short Course on Computational Complexity Theory, held at the Joint Mathematics Meetings in Atlanta in January 1988. The purpose of the short course was to provide an overview of complexity theory and to describe some of the current developments in the field. The papers presented here represent contributions by some of the top experts in this burgeoning area of research.

Computational Complexity

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Author: K. Wagner,G. Wechsung

Publisher: Springer

ISBN: 9027721467

Category: Computers

Page: 556

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Computational Complexity

A Conceptual Perspective

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Author: Oded Goldreich

Publisher: Cambridge University Press

ISBN: 1139472747

Category: Computers

Page: N.A

View: 6948

Complexity theory is a central field of the theoretical foundations of computer science. It is concerned with the general study of the intrinsic complexity of computational tasks; that is, it addresses the question of what can be achieved within limited time (and/or with other limited natural computational resources). This book offers a conceptual perspective on complexity theory. It is intended to serve as an introduction for advanced undergraduate and graduate students, either as a textbook or for self-study. The book will also be useful to experts, since it provides expositions of the various sub-areas of complexity theory such as hardness amplification, pseudorandomness and probabilistic proof systems. In each case, the author starts by posing the intuitive questions that are addressed by the sub-area and then discusses the choices made in the actual formulation of these questions, the approaches that lead to the answers, and the ideas that are embedded in these answers.

Computational Complexity and Statistical Physics

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Author: Allon Percus,Gabriel Istrate,Cristopher Moore

Publisher: Oxford University Press on Demand

ISBN: 9780195177374

Category: Computers

Page: 367

View: 6152

Computer science and physics have been closely linked since the birth of modern computing. In recent years, an interdisciplinary area has blossomed at the junction of these fields, connecting insights from statistical physics with basic computational challenges. Researchers have successfully applied techniques from the study of phase transitions to analyze NP-complete problems such as satisfiability and graph coloring. This is leading to a new understanding of the structure of these problems, and of how algorithms perform on them. Computational Complexity and Statistical Physics will serve as a standard reference and pedagogical aid to statistical physics methods in computer science, with a particular focus on phase transitions in combinatorial problems. Addressed to a broad range of readers, the book includes substantial background material along with current research by leading computer scientists, mathematicians, and physicists. It will prepare students and researchers from all of these fields to contribute to this exciting area.

Logic and Computational Complexity

International Workshop, LCC '94, Indianapolis, IN, USA, October 13-16, 1994. Selected Papers

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Author: International Workshop on Logic and Computational Complexity

Publisher: Springer Science & Business Media

ISBN: 9783540601784

Category: Computers

Page: 514

View: 9074

This book contains revised versions of papers invited for presentation at the International Workshop on Logic and Computational Complexity, LCC '94, held in Indianapolis, IN in October 1994. The synergy between logic and computational complexity has gained importance and vigor in recent years, cutting across many areas. The 25 revised full papers in this book contributed by internationally outstanding researchers document the state-of-the-art in this interdisciplinary field of growing interest; they are presented in sections on foundational issues, applicative and proof-theoretic complexity, complexity of proofs, computational complexity of functionals, complexity and model theory, and finite model theory.

Randomness and Completeness in Computational Complexity

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Author: Dieter van Melkebeek

Publisher: Springer Science & Business Media

ISBN: 9783540414926

Category: Computers

Page: 196

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This book is based on the author's Ph.D. thesis which was selected as the winning thesis of the 1999 ACM Doctoral Dissertation Competition. Dieter van Melkebeek did his Ph.D. work at the University of Chicago with Lance Fortnow as thesis advisor. This work studies some central issues in computational complexity: the relative power of time, space, and randomness in computing and verification. The author develops techniques for separating complexity classes by isolating structural differences between their complete problems. He presents several approaches based on such diverse concepts as density, redundancy, and frequency of occurrence.

Kolmogorov Complexity and Computational Complexity

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Author: Osamu Watanabe

Publisher: Springer Science & Business Media

ISBN: 364277735X

Category: Computers

Page: 105

View: 3732

The mathematical theory of computation has given rise to two important ap proaches to the informal notion of "complexity": Kolmogorov complexity, usu ally a complexity measure for a single object such as a string, a sequence etc., measures the amount of information necessary to describe the object. Compu tational complexity, usually a complexity measure for a set of objects, measures the compuational resources necessary to recognize or produce elements of the set. The relation between these two complexity measures has been considered for more than two decades, and may interesting and deep observations have been obtained. In March 1990, the Symposium on Theory and Application of Minimal Length Encoding was held at Stanford University as a part of the AAAI 1990 Spring Symposium Series. Some sessions of the symposium were dedicated to Kolmogorov complexity and its relations to the computational complexity the ory, and excellent expository talks were given there. Feeling that, due to the importance of the material, some way should be found to share these talks with researchers in the computer science community, I asked the speakers of those sessions to write survey papers based on their talks in the symposium. In response, five speakers from the sessions contributed the papers which appear in this book.