Proceedings Fifth Annual Structure in Complexity Theory Conference
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Publisher :
Page : 320 pages
File Size : 10,49 MB
Release : 1990
Category :
ISBN :
Author :
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Page : 320 pages
File Size : 10,49 MB
Release : 1990
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ISBN :
Author :
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Page : 320 pages
File Size : 26,99 MB
Release : 1990
Category : Algorithms
ISBN : 9780818690723
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Page : pages
File Size : 21,17 MB
Release : 1990
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Author : Structure in Complexity Theory Conference
Publisher :
Page : 320 pages
File Size : 46,3 MB
Release : 1990
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Author : Pennsy Acm Workshop on Computational Learning Theory 1992 Pittsburgh
Publisher : Assn for Computing Machinery
Page : 468 pages
File Size : 26,40 MB
Release : 1992
Category : Algorithms
ISBN : 9780897914970
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Page : 828 pages
File Size : 26,3 MB
Release : 1993
Category : Computation theory
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Author : Structure in Complexity Theory Conference (10, 1995, Minneapolis, Minn.)
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Page : 139 pages
File Size : 14,28 MB
Release : 1997
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Author :
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Page : 326 pages
File Size : 36,42 MB
Release : 1993
Category : Computational complexity
ISBN : 9780818640711
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Page : 468 pages
File Size : 43,47 MB
Release : 1992
Category : Algorithms
ISBN :
Author : Sanjeev Arora
Publisher : Cambridge University Press
Page : 519 pages
File Size : 47,68 MB
Release : 2009-04-20
Category : Computers
ISBN : 1139477366
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.