Computational Complexity And Local Algorithms
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Computational Complexity and Local Algorithms
This volume contains a collection of studies in the areas of complexity theory and local algorithms. A common theme in most of the papers is the interplay between randomness and computation. This interplay is pivotal to some parts of complexity theory and is essential for local algorithms. The works included address a variety of topics in the areas of complexity theory and local algorithms. Within complexity theory the topics include approximation algorithms, counting problems, enumeration problems, explicit construction of expander graphs, fine grained complexity, interactive proof systems, PPT-search and pseudodeterminism, space complexity, and worst-case to average-case reductions. Within local algorithms the focus is mostly on property testing and on locally testable and decodable codes. In particular, many of the works seek to advance the study of testing graph properties in the bounded-degree graph model. Other topics in property testing include testing group properties and testing properties of affine subspaces.
Computational Complexity
Author: Sanjeev Arora
language: en
Publisher: Cambridge University Press
Release Date: 2009-04-20
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.
Encyclopedia of Algorithms
Author: Ming-Yang Kao
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-08-06
One of Springer’s renowned Major Reference Works, this awesome achievement provides a comprehensive set of solutions to important algorithmic problems for students and researchers interested in quickly locating useful information. This first edition of the reference focuses on high-impact solutions from the most recent decade, while later editions will widen the scope of the work. All entries have been written by experts, while links to Internet sites that outline their research work are provided. The entries have all been peer-reviewed. This defining reference is published both in print and on line.