Titlebook: Randomization and Approximation Techniques in Computer Science; International Worksh José Rolim Conference proceedings 1997 Springer-Verlag

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书目名称Randomization and Approximation Techniques in Computer Science影响因子(影响力)




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书目名称Randomization and Approximation Techniques in Computer Science网络公开度学科排名




书目名称Randomization and Approximation Techniques in Computer Science被引频次




书目名称Randomization and Approximation Techniques in Computer Science被引频次学科排名




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书目名称Randomization and Approximation Techniques in Computer Science年度引用学科排名




书目名称Randomization and Approximation Techniques in Computer Science读者反馈




书目名称Randomization and Approximation Techniques in Computer Science读者反馈学科排名

NOCT

Approximation algorithms for covering polygons with squares and similar problems,ust lie entirely within the polygon. Let . be an arbitrary input polygon, with . vertices, coverable by squares. Let . denote the minimum number of squares required to cover .. In the first part of this paper we present an algorithm which guarantees a constant (14) approximation factor running in ..

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A combinatorial consistency lemma with application to proving the PCP theorem,egree tests. Here, we refer to the difficulty of obtaining . results regarding low-degree tests; namely, results of the type obtained and used by Arora and Safra and Arora et. al..In this paper, we eliminate the need to obtain such strong results on low-degree tests when proving the PCP Theorem. Alt

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Super-bits, demi-bits, and ,-natural proofs,l tests. This new kind of pseudo-randomness rules out the existence of .-natural properties that can work against .. This is an important extension of the original theory of .-natural proofs [10]. We also introduce the closely related demi-bit conjecture which is more intuitive and is the source of

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Serenity

Random-based scheduling new approximations and LP lower bounds,erage performance optimization. The general constrained one-machine scheduling problem to minimize the average weighted completion time not only captures these features, but also is an important building block for more complex problems involving multiple machines..In this context, the conversion of

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chiropractor

Probabilistic approximation of some NP optimization problems by finite-state machines,t with probability tending to 1 as the number of input items tends to infinity, the problem is approximable up to any given constant factor ε > 0 by a finite-state machine. More precisely, let . be a problem in our subclass of NP optimization problems, and let . be an input represented by a sequence

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