Titlebook: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques; 12th International W Irit Dinur,Klaus Jansen,José

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書目名稱Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques被引頻次




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書目名稱Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques讀者反饋




書目名稱Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques讀者反饋學(xué)科排名

車床

Lice692

Approximations for Aligned Coloring and Spillage Minimization in Interval and Chordal Graphspilers and have recently been proven NP-Hard. We provide the first constant approximations: a .-approximation for interval graphs and a .-approximation for chordal graphs. We extend our techniques to the problem of minimizing spillage in these graph types.

CHECK

閹割

Truthful Mechanisms via Greedy Iterative Packinge. A fundamental question is whether an .-approximation algorithm translates into an .-approximate truthful mechanism. It is well-known that plugging an .-approximation algorithm into the VCG technique may not yield a truthful mechanism. Thus, it is natural to investigate properties of approximation

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哺乳動物

Entreaty

New Hardness Results for Diophantine Approximationsion of this problem consists of a rational vector .?∈??., an error bound . and a denominator bound .?∈??.. One has to decide whether there exists an integer, called the.. with 1?≤?.?≤?. such that the distance of each number . ·.. to its nearest integer is bounded by .. Lagarias has shown that this

代替

PASS Approximationtandard worst-case analysis. We circumvent such negative results by designing guarantees for classes of instances, parameterized according to properties of the optimal solution. We also make sure that our parameterized approximation, called . approximation, is the best possible. We show how to apply

祖先

Optimal Sherali-Adams Gaps from Pairwise Independenceted by . contains the support of a balanced pairwise independent distribution over the domain of the inputs, then such a problem on . variables cannot be approximated better than the trivial (random) approximation, even using Ω(.) levels of the Sherali-Adams LP hierarchy..It was recently shown [3] t