A. Fiat and M. Mendel. Better algorithms for unfair metrical task systems and applications. In Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, pages 725-734, 2000. Home/Search Document Details and Download
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On-Line Algorithms And Fast Digital Identity Revocation - Lodha (Correct)
....M , is called a schedule for x 0 , # . We define cost(x 0 , # , x) m X i=1 [x i 1 x i # i (x i ) opt(x 0 , #) min x cost(x 0 , # , x) The goal is design an on line strategy that would have minimum possible competitive ratio when compared with opt. In a series of papers [2, 4, 5, 6, 25], a powerful method was developed for the randomized MTS problem. Translating these results for the k server problem, the smallest randomized competitive ratio for general metric spaces is min(2k 1, O(log n k log log n k log n log log n) see [25] Note that## q log k ....
....of papers [2, 4, 5, 6, 25] a powerful method was developed for the randomized MTS problem. Translating these results for the k server problem, the smallest randomized competitive ratio for general metric spaces is min(2k 1, O(log n k log log n k log n log log n) see [25]. Note that## q log k loglogk ) lower bound is given in [14] for the competitive ratio in general metric spaces. Here we investigate the randomized k server problem for the special case when the underlying metric space is given by n equally spaced points on a line. The case when the metric ....
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A. Fiat and M. Mendel. Better algorithms for unfair metrical task systems and applications. In Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, pages 725--734, 2000.
A Randomized On-line Algorithm for the k-Server Problem on a Line - Csaba, al. (2001) (1 citation) (Correct)
....case for which there is a good randomized on line algorithm is the case of p(n) unbalanced metric spaces [6] For general metric spaces, the best results so far were achieved by the help of randomized algorithms for the metrical task system problem. In a series of papers ( 1] 2] 3] and [9]) a powerful method was developed for the randomized MTS problem. Translating these results for the k server problem, the smallest randomized competitive ratio for general metric spaces is min(2k 1,O(log n k log log n k log n log log n) see [9] Note that## q log k loglogk ) ....
....of papers ( 1] 2] 3] and [9] a powerful method was developed for the randomized MTS problem. Translating these results for the k server problem, the smallest randomized competitive ratio for general metric spaces is min(2k 1,O(log n k log log n k log n log log n) see [9]. Note that## q log k loglogk ) lower bound is given in [6] for the competitive ratio in general metric spaces. Here we investigate the randomized k server problem for the special case when the underlying metric space is given by n equally spaced points on a line. The case when the metric ....
[Article contains additional citation context not shown here]
A. Fiat and M. Mendel. Better algorithms for unfair metrical task systems and applications. In Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, pages 725--734, 2000.
A General Decomposition Theorem for the k-Server Problem - Seiden (2001) (2 citations) (Correct)
....Chrobak and Larmore [4] For the case where we have a # Address: Department of Computer Science, 298 Coates Hall, Louisiana State University, Baton Rouge, LA 70803. Email: sseiden acm.org 1 finite metric with k 1 points, the problem is closely related to the metrical task system (MTS) problem [10, 3, 16]. The results on that problem imply that there is a O(polylog(k) competitive algorithm for every finite space with k 1 points. A O(log k) competitive algorithm for the weighted cache problem with 2 weights has recently been exhibited by Irani [18] In summary, the only two metrics for which a ....
....sub spaces. The theorem may be applied recursively. As we shall argue in the next section, we feel that this is the first step towards a resolution of the randomized conjecture. Another important contribution of this work is in illustrating the usefulness of unfair metrical task systems (UMTS) [24, 3, 16] as a general algorithmic design tool. Unfair metrical task systems allow us to design divide and conquer online algorithms. As far as we know, this work is the first application of the UMTS technique outside of the metrical task system problem. 2 A Line of Attack on the k server Conjecture As ....
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Fiat, A., and Mendel, M. Better algorithms for unfair metrical task systems and applications. In Proceedings of the 32nd Annual ACM Symposium on Theory of Computing (May 2000), pp. 725--734.
Randomized k-Server Algorithms for Growth-Rate Bounded Graphs.. - Yair Cs Huji (2003) Self-citation (Mendel) (Correct)
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Amos Fiat and Manor Mendel. Better algorithms for unfair metrical task systems and applications. In Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, pages 725--734, May 2000.
Multi-Embedding and Path Approximation of Metric Spaces - Yair Bartal Manor (2003) (1 citation) Self-citation (Mendel) (Correct)
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A. Fiat and M. Mendel. Better algorithms for unfair metrical task systems and applications. In Proceedings of the 32nd STOC, pages 725-734, 2000.
A Ramsey-type Theorem for Metric Spaces and its.. - Bartal.. (2001) (1 citation) Self-citation (Mendel) (Correct)
....lower bounds were e 1 log n) KRR94] and log n= log log n) BKRS00] for MTS and similar lower bounds for K server in n point space, when n K. Our paper improve these lower bounds, following major advancements in the analysis of the upper bounds for MTS, appearing in [Bar96, Bar98, BBBT97, FM00] The best current upper bound for MTS is O(log n log log n) Currently there is no general randomized upper bound for the K server problem better than 2K 1 [KP95] Seiden [Sei01] has a promising result in this direction, showing sub linear bounds for certain spaces with certain number of ....
....the expectation of the distances. In [Bar96, Bar98] it is proved that any metric space on n points can be O(log n log log n) probabilistically approximated by an HST, thus reducing the problem of devising algorithm for MTS on any metric space to devising an algorithm for HSTs only [BBBT97, FM00] HSTs and their probabilistic approximation of metric spaces have found many other applications in online and approximation algorithms, for example [Bar96, AA97, CCG 98, CR98, GKR00, WLB 99, KPR99, KT99, KR00, CKNlZ01, BCR01] The rst step toward obtaining a lower bound for arbitrary ....
[Article contains additional citation context not shown here]
Amos Fiat and Manor Mendel, Better algorithms for unfair metrical task systems and applications, Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, May 2000, pp. 725-734.
A Theoretical Study of Optimization Techniques Used in - Registration Area Based (Correct)
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A. Fiat and M. Mendel. Better algorithms for unfair metrical task systems and applications. In Proceedings of the 32nd Annual ACM Symposium on Theory of Computing, pages 725-734, 2000.
A Tight Bound on Approximating Arbitrary Metrics by Tree.. - Fakcharoenphol, Rao.. (2003) (14 citations) (Correct)
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A. Fiat and M. Mendel. Better algorithms for unfair metrical task systems and applications. In Proceedings of the 32nd STOC, pages 725-734, 2000.
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