Algorithm Theory - SWAT 2004: 9th Scandinavian Workshop on - download pdf or read online

By Charles E. Leiserson (auth.), Torben Hagerup, Jyrki Katajainen (eds.)

ISBN-10: 3540223398

ISBN-13: 9783540223399

ISBN-10: 3540278109

ISBN-13: 9783540278108

This publication constitutes the refereed court cases of the ninth Scandinavian Workshop on set of rules idea, SWAT 2004, held in Humlebaek, Denmark in July 2004.

The forty revised complete papers provided including an invited paper and the summary of an invited speak have been rigorously reviewed and chosen from 121 submissions. The papers span the full variety of theoretical algorithmics and purposes in a variety of fields together with graph algorithms, computational geometry, scheduling, approximation algorithms, community algorithms, information garage and manipulation, bioinformatics, combinatorics, sorting, looking, on-line algorithms, optimization, etc.

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Read or Download Algorithm Theory - SWAT 2004: 9th Scandinavian Workshop on Algorithm Theory, Humlebæk, Denmark, July 8-10, 2004. Proceedings PDF

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Additional info for Algorithm Theory - SWAT 2004: 9th Scandinavian Workshop on Algorithm Theory, Humlebæk, Denmark, July 8-10, 2004. Proceedings

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Yao, A Demers, and S. Shenker. A scheduling model for reduced cpu energy. In IEEE Symposium on Foundations of Computer Science, pages 374–382, 1995. il Abstract. In a combinatorial auction k different items are sold to n bidders, where the objective of the seller is to maximize the revenue. The main difficulty to find an optimal allocation is due to the fact that the valuation function of each bidder for bundles of items is not necessarily an additive function over the items. An auction with budget constraints is a common special case where bidders generally have additive valuations, yet they have a limit on their maximal valuation.

The contribution of X ˆi1 = bi1 xi1 1 − Zi1 ≤ 1, so the expected marginal contribution is at most x 2. If 1 − bi1 < Zi1 ≤ 1: The marginal contribution of both variables is either 0 or 1 − Zi1 . The expected marginal contribution of Xi1 is (1 − Zi1 )xi1 . The ˆ i1 is (1 − Zi1 )xi1 bi1 ≤ (1 − Zi1 )xi1 . expected marginal contribution of X ˆ i1 we can only decrease E(Zi ), without In both cases, by replacing Xi1 with X changing Bi . Similarly, for each 2 ≤ j ≤ r we replace bij with ˆbij = 1, xij with ˆ ij .

References 1. K. Azar. Managing power requirements in the electronics industry. Electronics Cooling Magazine, 6(4), 2000. 2. D. Brooks, P. Bose, S. Schuster, H. Jacobson, P. Kudva, A. Buyuktosunoglu, J. Wellman, V. Zyuban, M. Gupta, and P. Cook. Power-aware microarchitecture: design and modeling challenges for next generation microprocessors. IEEE Micro, 20(6), 2000. 3. D. Grunwald, P. Lewis, and K. Farkas. Policies for dynamic clock scheduling. In USENIX Symposium on Operating Systems Design and Implementation, 2000.

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Algorithm Theory - SWAT 2004: 9th Scandinavian Workshop on Algorithm Theory, Humlebæk, Denmark, July 8-10, 2004. Proceedings by Charles E. Leiserson (auth.), Torben Hagerup, Jyrki Katajainen (eds.)

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