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On the Competitive Ratio of Online Sampling
"... Abstract. We study online profitmaximizing auctions for digital goods with adversarial bid selection and uniformly random arrivals. Our goal is to design auctions that are constant competitive with F (2) ; in this sense our model lies at the intersection of priorfree mechanism design and secretary ..."
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and secretary problems. We first give a generic reduction that transforms any offline auction to an online one, with only a loss of a factor of 2 in the competitive ratio; we then present some natural auctions, both randomized and deterministic, and study their competitive ratio; our analysis reveals some
Thoughts on the Competitive Ratio
"... An algorithm for a typical combinatorial optimization problem is given static input, and finds a single solution. Incremental optimization is one framework for handling problems that require solutions to be built up over time due to evolving constraints. An incremental algorithm is given a sequence ..."
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Cited by 1 (0 self)
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. Thus two factors can affect the competitive ratio of an online problem: that it does not know the input sequence in advance, and that it makes irreversible decisions. Both factors contribute to an algorithm’s performance, but the competitive ratio fails to discern which is more significant. Incremental
On the Competitive Ratio of the Random Sampling Auction
 In Proc. 1st Workshop on Internet and Network Economics
, 2005
"... Abstract. We give a simple analysis of the competitive ratio of the random sampling auction from [10]. The random sampling auction was first shown to be worstcase competitive in [9] (with a bound of 7600 on its competitive ratio); our analysis improves the bound to 15. In support of the conjecture ..."
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Cited by 28 (8 self)
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Abstract. We give a simple analysis of the competitive ratio of the random sampling auction from [10]. The random sampling auction was first shown to be worstcase competitive in [9] (with a bound of 7600 on its competitive ratio); our analysis improves the bound to 15. In support of the conjecture
On the competitive ratio for online facility location
 In ICALP
, 2003
"... Abstract. We consider the problem of Online Facility Location, where demands arrive online and must be irrevocably assigned to an open facility upon arrival. The objective is to minimize the sum of facility and assignment costs. We prove that the competitive log n ratio for Online Facility Location ..."
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Cited by 23 (2 self)
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Abstract. We consider the problem of Online Facility Location, where demands arrive online and must be irrevocably assigned to an open facility upon arrival. The objective is to minimize the sum of facility and assignment costs. We prove that the competitive log n ratio for Online Facility Location
Separating the Accommodating Ratio from the Competitive Ratio
, 1999
"... It is shown that for the Unit Price Bin Packing problem, WorstFit has a strictly better competitive ratio than FirstFit. With respect to this problem, FirstFit has previously been proven to have a better accommodating ratio than WorstFit. This shows that the accommodating ratio can give differen ..."
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Cited by 2 (2 self)
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It is shown that for the Unit Price Bin Packing problem, WorstFit has a strictly better competitive ratio than FirstFit. With respect to this problem, FirstFit has previously been proven to have a better accommodating ratio than WorstFit. This shows that the accommodating ratio can give
On the competitive ratio of evaluating priced functions
 In Proceedings of the seventeenth Annual ACMSIAM Symposium on Discrete Algorithms (SODA06
, 2006
"... Let f be a function on a set of variables V. For each x ∈ V, let c(x) be the cost of reading the value of x. An algorithm for evaluating f is a strategy for adaptively identifying and reading a set of variables U ⊆ V whose values uniquely determine the value of f. We are interested in finding algori ..."
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Cited by 5 (2 self)
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(x), for each x ∈ V. For the case where f is a monotone boolean function which is representable by a threshold tree, we provide a polynomial time algorithm with the best possible competitive ratio γfc for each fixed cost function c(·). Remarkably, the best known result for the same class of functions is a
A Lower Bound on the Competitive Ratio of Truthful Auctions
 In Proceedings 21st Symposium on Theoretical Aspects of Computer Science
, 2004
"... Abstract We study a class of singleround, sealedbid auctions for a set of identical items. We adopt the worst case competitive framework defined by [1,2] that compares the profit of an auction to that of an optimal single price sale to at least two bidders. In this framework, we give a lower bound ..."
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Cited by 13 (5 self)
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bound of 2.42 (an improvement from the bound of 2 given in [2]) on the competitive ratio of any truthful auction, one where each bidders best strategy is to declare the true maximum value an item is worth to them. This result contrasts with the 3.39 competitive ratio of the best known truthful auction
Improved Competitive Ratio for the Matroid Secretary Problem
"... The Matroid Secretary Problem, introduced by Babaioff et al. (2007), is a generalization of the Classical Secretary Problem. In this problem, elements from a matroid are presented to an online algorithm in a random order. Each element has a weight associated with it, which is revealed to the algori ..."
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Cited by 5 (0 self)
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Secretary Problem with a competitive ratio of O(logρ), where ρ is the rank of the matroid. It has been conjectured that a constant competitiveratio is achievable for this problem. In this paper we give an algorithm that has a competitiveratio of O ( √ logρ). 1
Buying a Constant Competitive Ratio for Paging
"... We consider a variant of the online paging problem where the online algorithm may buy additional cache slots at a certain cost. The overall cost incurred equals the total cost for the cache plus the number of page faults. This problem and our results are a generalization of both, the classical pagin ..."
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paging problem and the ski rental problem. We derive the following three tight results: (1) For the case where the cache cost depends linearly on the cache size, we give a competitive online algorithm where 3.14619 is a solution of = 2+ln . This competitive ratio is best possible. (2) For the case where
The Accommodating Function  a generalization of the competitive ratio
 In Sixth International Workshop on Algorithms and Data Structures, volume 1663 of Lecture Notes in Computer Science
, 1998
"... A new measure, the accommodating function, for the quality of online algorithms is presented. The accommodating function, which is a generalization of both the competitive ratio and the accommodating ratio, measures the quality of an online algorithm as a function of the resources that would be su ..."
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Cited by 17 (10 self)
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A new measure, the accommodating function, for the quality of online algorithms is presented. The accommodating function, which is a generalization of both the competitive ratio and the accommodating ratio, measures the quality of an online algorithm as a function of the resources that would
Results 1  10
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