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Worstcase equilibria
 IN PROCEEDINGS OF THE 16TH ANNUAL SYMPOSIUM ON THEORETICAL ASPECTS OF COMPUTER SCIENCE
, 1999
"... In a system in which noncooperative agents share a common resource, we propose the ratio between the worst possible Nash equilibrium and the social optimum as a measure of the effectiveness of the system. Deriving upper and lower bounds for this ratio in a model in which several agents share a ver ..."
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Cited by 851 (17 self)
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In a system in which noncooperative agents share a common resource, we propose the ratio between the worst possible Nash equilibrium and the social optimum as a measure of the effectiveness of the system. Deriving upper and lower bounds for this ratio in a model in which several agents share a very simple network leads to some interesting mathematics, results, and open problems.
The Omega Test: a fast and practical integer programming algorithm for dependence analysis
 Communications of the ACM
, 1992
"... The Omega testi s ani nteger programmi ng algori thm that can determi ne whether a dependence exi sts between two array references, and i so, under what condi7: ns. Conventi nalwi[A m holds thati nteger programmiB techni:36 are far too expensi e to be used for dependence analysi6 except as a method ..."
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Cited by 521 (15 self)
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programs, the average ti me requi red by the Omega test to determi ne the di recti on vectors for an array pai ri s less than 500 secs on a 12 MIPS workstati on. The Omega testi based on an extensi n of Four i0Motzki var i ble eli937 ti n (aliB: r programmiA method) toi nteger programmi ng, and has worstcase
Improved Approximation Algorithms for Maximum Cut and Satisfiability Problems Using Semidefinite Programming
 Journal of the ACM
, 1995
"... We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a simple and elegant technique that randomly rounds the solution ..."
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Cited by 1231 (13 self)
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We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least .87856 times the optimal value. These algorithms use a simple and elegant technique that randomly rounds the solution to a nonlinear programming relaxation. This relaxation can be interpreted both as a semidefinite program and as an eigenvalue minimization problem. The best previously known approximation algorithms for these problems had performance guarantees of ...
A Scheme for RealTime Channel Establishment in WideArea Networks
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 1990
"... Multimedia communication involving digital audio and/or digital video has rather strict delay requirements. A realtime channel is defined in this paper as a simplex connection between a source and a destination characterized by parameters representing the performance requirements of the client. A r ..."
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Cited by 710 (31 self)
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Multimedia communication involving digital audio and/or digital video has rather strict delay requirements. A realtime channel is defined in this paper as a simplex connection between a source and a destination characterized by parameters representing the performance requirements of the client. A realtime service is capable of creating realtime channels on demand and guaranteeing their performance. These guarantees often take the form of lower bounds on the bandwidth allocated to a channel and upper bounds on the delays to be experienced by a packet on the channel. In this paper
Receiverdriven Layered Multicast
, 1996
"... State of the art, realtime, rateadaptive, multimedia applications adjust their transmission rate to match the available network capacity. Unfortunately, this sourcebased rateadaptation performs poorly in a heterogeneous multicast environment because there is no single target rate — the conflicti ..."
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Cited by 749 (22 self)
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State of the art, realtime, rateadaptive, multimedia applications adjust their transmission rate to match the available network capacity. Unfortunately, this sourcebased rateadaptation performs poorly in a heterogeneous multicast environment because there is no single target rate — the conflicting bandwidth requirements of all receivers cannot be simultaneously satisfied with one transmission rate. If the burden of rateadaption is moved from the source to the receivers, heterogeneity is accommodated. One approach to receiverdriven adaptation is to combine a layered source coding algorithm with a layered transmission system. By selectively forwarding subsets of layers at constrained network links, each user receives the best quality signal that the network can deliver. We and others have proposed that selectiveforwarding be carried out using multiple IPMulticast groups where each receiver specifies its level of subscription by joining a subset of the groups. In this paper, we extend the multiple group framework with a rateadaptation protocol called Receiverdriven Layered Multicast, or RLM. Under RLM, multicast receivers adapt to both the static heterogeneity of link bandwidths as well as dynamic variations in network capacity (i.e., congestion). We describe the RLM protocol and evaluate its performance with a preliminary simulation study that characterizes userperceived quality by assessing loss rates over multiple time scales. For the configurations we simulated, RLM results in good throughput with transient shortterm loss rates on the order of a few percent and longterm loss rates on the order of one percent. Finally, we discuss our implementation of a softwarebased Internet video codec and its integration with RLM.
Learning the Kernel Matrix with SemiDefinite Programming
, 2002
"... Kernelbased learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information ..."
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Cited by 780 (22 self)
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Kernelbased learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the socalled kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input spaceclassical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques. When applied
Supporting RealTime Applications in an Integrated Services Packet Network: Architecture and Mechanism
, 1992
"... This paper considers the support of realtime applications in an ..."
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Cited by 575 (25 self)
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This paper considers the support of realtime applications in an
How bad is selfish routing?
 JOURNAL OF THE ACM
, 2002
"... We consider the problem of routing traffic to optimize the performance of a congested network. We are given a network, a rate of traffic between each pair of nodes, and a latency function for each edge specifying the time needed to traverse the edge given its congestion; the objective is to route t ..."
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Cited by 678 (27 self)
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We consider the problem of routing traffic to optimize the performance of a congested network. We are given a network, a rate of traffic between each pair of nodes, and a latency function for each edge specifying the time needed to traverse the edge given its congestion; the objective is to route traffic such that the sum of all travel times—the total latency—is minimized. In many settings, it may be expensive or impossible to regulate network traffic so as to implement an optimal assignment of routes. In the absence of regulation by some central authority, we assume that each network user routes its traffic on the minimumlatency path available to it, given the network congestion caused by the other users. In general such a “selfishly motivated ” assignment of traffic to paths will not minimize the total latency; hence, this lack of regulation carries the cost of decreased network performance. In this article, we quantify the degradation in network performance due to unregulated traffic. We prove that if the latency of each edge is a linear function of its congestion, then the total latency of the routes chosen by selfish network users is at most 4/3 times the minimum possible total latency (subject to the condition that all traffic must be routed). We also consider the more general setting in which edge latency functions are assumed only to be continuous and nondecreasing in the edge congestion. Here, the total
A Guided Tour to Approximate String Matching
 ACM COMPUTING SURVEYS
, 1999
"... We survey the current techniques to cope with the problem of string matching allowing errors. This is becoming a more and more relevant issue for many fast growing areas such as information retrieval and computational biology. We focus on online searching and mostly on edit distance, explaining t ..."
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Cited by 584 (38 self)
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We survey the current techniques to cope with the problem of string matching allowing errors. This is becoming a more and more relevant issue for many fast growing areas such as information retrieval and computational biology. We focus on online searching and mostly on edit distance, explaining the problem and its relevance, its statistical behavior, its history and current developments, and the central ideas of the algorithms and their complexities. We present a number of experiments to compare the performance of the different algorithms and show which are the best choices according to each case. We conclude with some future work directions and open problems.
Results 1  10
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68,861