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020 _a1423709357 (electronic bk.)
020 _a9781423709350 (electronic bk.)
020 _a9780444828415
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020 _a008047666X (electronic bk.)
020 _a9780080476667 (electronic bk.)
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035 _a(OCoLC)60747122
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_z(OCoLC)441778489
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_bElsevier Science & Technology
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082 0 4 _a511.352
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049 _aTEFA
100 1 _aZimand, Marius.
245 1 0 _aComputational complexity
_h[electronic resource] :
_ba quantitative perspective /
_cMarius Zimand.
250 _a1st ed.
260 _aAmsterdam ;
_aBoston :
_bElsevier,
_c2004.
300 _a1 online resource (xii, 340 pages).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aNorth-Holland mathematics studies,
_x0304-0208 ;
_v196
504 _aIncludes bibliographical references (pages 321-332) and index.
588 0 _aPrint version record.
505 0 _aContents -- Preface. -- 1. Preliminaries. -- 2. Abstract complexity theory. -- 3. P, NP, and E. -- 4. Quantum computation. -- 5. One-way functions, pseudo-random generators. -- 6. Optimization problems. -- A. Tail bounds. -- Bibliography. -- Index.
520 _aThere has been a common perception that computational complexity is a theory of "bad news" because its most typical results assert that various real-world and innocent-looking tasks are infeasible. In fact, "bad news" is a relative term, and, indeed, in some situations (e.g., in cryptography), we want an adversary to not be able to perform a certain task. However, a "bad news" result does not automatically become useful in such a scenario. For this to happen, its hardness features have to be quantitatively evaluated and shown to manifest extensively. The book undertakes a quantitative analysis of some of the major results in complexity that regard either classes of problems or individual concrete problems. The size of some important classes are studied using resource-bounded topological and measure-theoretical tools. In the case of individual problems, the book studies relevant quantitative attributes such as approximation properties or the number of hard inputs at each length. One chapter is dedicated to abstract complexity theory, an older field which, however, deserves attention because it lays out the foundations of complexity. The other chapters, on the other hand, focus on recent and important developments in complexity. The book presents in a fairly detailed manner concepts that have been at the centre of the main research lines in complexity in the last decade or so, such as: average-complexity, quantum computation, hardness amplification, resource-bounded measure, the relation between one-way functions and pseudo-random generators, the relation between hard predicates and pseudo-random generators, extractors, derandomization of bounded-error probabilistic algorithms, probabilistically checkable proofs, non-approximability of optimization problems, and others. The book should appeal to graduate computer science students, and to researchers who have an interest in computer science theory and need a good understanding of computational complexity, e.g., researchers in algorithms, AI, logic, and other disciplines. Emphasis is on relevant quantitative attributes of important results in complexity. Coverage is self-contained and accessible to a wide audience. Large range of important topics including: derandomization techniques, non-approximability of optimization problems, average-case complexity, quantum computation, one-way functions and pseudo-random generators, resource-bounded measure and topology.
650 0 _aComputational complexity.
650 7 _aCOMPUTERS
_xMachine Theory.
_2bisacsh
650 7 _aComputational complexity.
_2fast
_0(OCoLC)fst00871991
655 4 _aElectronic books.
776 0 8 _iPrint version:
_aZimand, Marius.
_tComputational complexity.
_b1st ed.
_dAmsterdam ; Boston : Elsevier, 2004
_z0444828419
_w(OCoLC)56057801
830 0 _aNorth-Holland mathematics studies ;
_v196.
_x0304-0208
856 4 0 _3ScienceDirect
_uhttp://www.sciencedirect.com/science/book/9780444828415
856 4 0 _3ScienceDirect
_uhttp://www.sciencedirect.com/science/publication?issn=03040208&volume=196
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