Results 1  10
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Fibonacci Heaps and Their Uses in Improved Network . . .
, 1987
"... In this paper we develop a new data structure for implementing heaps (priority queues). Our structure, Fibonacci heaps (abbreviated Fheaps), extends the binomial queues proposed by Vuillemin and studied further by Brown. Fheaps support arbitrary deletion from an nitem heap in qlogn) amortized t ..."
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Cited by 746 (18 self)
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time and all other standard heap operations in o ( 1) amortized time. Using Fheaps we are able to obtain improved running times for several network optimization algorithms. In particular, we obtain the following worstcase bounds, where n is the number of vertices and m the number of edges
Improved bounds for mixing rates of Markov chains and multicommodity flow
 Combinatorics, Probability and Computing
, 1992
"... The paper is concerned with tools for the quantitative analysis of finite Markov chains whose states are combinatorial structures. Chains of this kind have algorithmic applications in many areas, including random sampling, approximate counting, statistical physics and combinatorial optimisation. The ..."
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Cited by 211 (8 self)
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viewed as a graph. The bound gives sharper estimates for the mixing rate of several important complex Markov chains. As a result, improved bounds are obtained for the runtimes of randomised approximation algorithms for various problems, including computing the permanent of a 01 matrix, counting
Theoretical improvements in algorithmic efficiency for network flow problems

, 1972
"... This paper presents new algorithms for the maximum flow problem, the Hitchcock transportation problem, and the general minimumcost flow problem. Upper bounds on ... the numbers of steps in these algorithms are derived, and are shown to compale favorably with upper bounds on the numbers of steps req ..."
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Cited by 565 (0 self)
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This paper presents new algorithms for the maximum flow problem, the Hitchcock transportation problem, and the general minimumcost flow problem. Upper bounds on ... the numbers of steps in these algorithms are derived, and are shown to compale favorably with upper bounds on the numbers of steps
Improved bounds for computing kemeny rankings
 In AAAI’06, 620–626
, 2006
"... Voting (or rank aggregation) is a general method for aggregating the preferences of multiple agents. One voting rule of particular interest is the Kemeny rule, which minimizes the number of cases where the final ranking disagrees with a vote on the order of two alternatives. Unfortunately, Kemeny r ..."
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Cited by 54 (8 self)
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rankings are NPhard to compute. Recent work on computing Kemeny rankings has focused on producing good bounds to use in searchbased methods. In this paper, we extend on this work by providing various improved bounding techniques. Some of these are based on cycles in the pairwise majority graph, others
Improved Bounds on the Sample Complexity of Learning
 Journal of Computer and System Sciences
, 2000
"... We present two improved bounds on the sample complexity of learning. First, we present a new general upper bound on the number of examples required to estimate all of the expectations of a set of random variables uniformly well. The quality of the estimates is measured using a variant of the relativ ..."
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Cited by 53 (1 self)
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We present two improved bounds on the sample complexity of learning. First, we present a new general upper bound on the number of examples required to estimate all of the expectations of a set of random variables uniformly well. The quality of the estimates is measured using a variant
Making the most of statistical analyses: Improving interpretation and presentation
 American Journal of Political Science
, 2000
"... Social scientists rarely take full advantage of the information available in their statistical results. As a consequence, they miss opportunities to present quantities that are of greatest substantive interest for their research and express the appropriate degree of certainty about these quantities. ..."
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Cited by 550 (24 self)
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Social scientists rarely take full advantage of the information available in their statistical results. As a consequence, they miss opportunities to present quantities that are of greatest substantive interest for their research and express the appropriate degree of certainty about these quantities. In this article, we offer an approach, built on the technique of statistical simulation, to extract the currently overlooked information from any statistical method and to interpret and present it in a readerfriendly manner. Using this technique requires some expertise,
Improved bounds for testing juntas
 In Proc. 12th Workshop RANDOM
, 2008
"... Abstract. We consider the problem of testing functions for the property of being a kjunta (i.e., of depending on at most k variables). Fischer, Kindler, Ron, Safra, and Samorodnitsky (J. Comput. Sys. Sci., 2004) showed that Õ(k2)/ɛ queries are sufficient to test kjuntas, and conjectured that this ..."
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Cited by 13 (5 self)
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that this bound is optimal for nonadaptive testing algorithms. Our main result is a nonadaptive algorithm for testing kjuntas with Õ(k 3/2)/ɛ queries. This algorithm disproves the conjecture of Fischer et al. We also show that the query complexity of nonadaptive algorithms for testing juntas has a lower bound
An improved bound on distillable entanglement
 In LANL eprint quantph/9809082
, 1999
"... Abstract. The best bound known on 2locally distillable entanglement is that of Vedral and Plenio, involving a certain measure of entanglement based on relative entropy. It turns out that a related argument can be used to give an even stronger bound; we give this bound, and examine some of its prope ..."
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Cited by 10 (1 self)
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Abstract. The best bound known on 2locally distillable entanglement is that of Vedral and Plenio, involving a certain measure of entanglement based on relative entropy. It turns out that a related argument can be used to give an even stronger bound; we give this bound, and examine some of its
Improved algorithms for optimal winner determination in combinatorial auctions and generalizations
, 2000
"... Combinatorial auctions can be used to reach efficient resource and task allocations in multiagent systems where the items are complementary. Determining the winners is NPcomplete and inapproximable, but it was recently shown that optimal search algorithms do very well on average. This paper present ..."
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Cited by 598 (55 self)
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presents a more sophisticated search algorithm for optimal (and anytime) winner determination, including structural improvements that reduce search tree size, faster data structures, and optimizations at search nodes based on driving toward, identifying and solving tractable special cases. We also uncover
Results 1  10
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