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Faster Algorithms for AllPairs Small Stretch Distances in Weighted Graphs
"... Abstract. Let G = (V,E) be a weighted undirected graph, with nonnegative edge weights. We consider the problem of efficiently computing approximate distances between all pairs of vertices in G. While many efficient algorithms are known for this problem in unweighted graphs, not many results are kno ..."
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Cited by 1 (0 self)
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of vertices. It is known that finding distances of stretch less than 2 between all pairs of vertices in G is at least as hard as Boolean matrix multiplication of two n×n matrices. It is also known that allpairs stretch 3 distances can be computed in Õ(n 2) time and allpairs stretch 7/3 distances can
AllPairs SmallStretch Paths
 Journal of Algorithms
, 1997
"... Let G = (V; E) be a weighted undirected graph. A path between u; v 2 V is said to be of stretch t if its length is at most t times the distance between u and v in the graph. We consider the problem of finding smallstretch paths between all pairs of vertices in the graph G. It is easy to see that f ..."
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Cited by 39 (7 self)
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Let G = (V; E) be a weighted undirected graph. A path between u; v 2 V is said to be of stretch t if its length is at most t times the distance between u and v in the graph. We consider the problem of finding smallstretch paths between all pairs of vertices in the graph G. It is easy to see
AllPairs SmallStretch Paths
"... Abstract Let G = (V; E) be a weighted undirected graph. A path between u; v 2 V is said to be of stretch t if its length is at most t times the distance between u and v in the graph. We consider the problem of finding smallstretch paths between all pairs of vertices in the graph G. It is easy to se ..."
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Abstract Let G = (V; E) be a weighted undirected graph. A path between u; v 2 V is said to be of stretch t if its length is at most t times the distance between u and v in the graph. We consider the problem of finding smallstretch paths between all pairs of vertices in the graph G. It is easy
Faster Algorithms for Approximate Distance Oracles and AllPairs Small StretchPaths
"... ffi(u, v) < = ^ffi(u, v) < = t * ffi(u, v). The most efficient algorithms known for computing small stretch distances in Gare the approximate distance oracles of [16] and the three algorithms in [9] to compute allpairs stretch t distancesfor t = 2, 7/3, and 3. We present faster algorithms fo ..."
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ffi(u, v) < = ^ffi(u, v) < = t * ffi(u, v). The most efficient algorithms known for computing small stretch distances in Gare the approximate distance oracles of [16] and the three algorithms in [9] to compute allpairs stretch t distancesfor t = 2, 7/3, and 3. We present faster algorithms
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
Scalable Application Layer Multicast
, 2002
"... We describe a new scalable applicationlayer multicast protocol, specifically designed for lowbandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the applicationlayer multicast peers and can support a number of different data deliv ..."
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Cited by 719 (21 self)
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We describe a new scalable applicationlayer multicast protocol, specifically designed for lowbandwidth, data streaming applications with large receiver sets. Our scheme is based upon a hierarchical clustering of the applicationlayer multicast peers and can support a number of different data delivery trees with desirable properties. We present extensive simulations of both our protocol and the Narada applicationlayer multicast protocol over Internetlike topologies. Our results show that for groups of size 32 or more, our protocol has lower link stress (by about 25%), improved or similar endtoend latencies and similar failure recovery properties. More importantly, it is able to achieve these results by using orders of magnitude lower control traffic. Finally, we present results from our widearea testbed in which we experimented with 32100 member groups distributed over 8 different sites. In our experiments, averagegroup members established and maintained lowlatency paths and incurred a maximum packet loss rate of less than 1 % as members randomly joined and left the multicast group. The average control overhead during our experiments was less than 1 Kbps for groups of size 100.
Detecting Pedestrians Using Patterns of Motion and Appearance
 IN ICCV
, 2003
"... This paper describes a pedestrian detection system that integrates image intensity information with motion information. We use a detection style algorithm that scans a detector over two consecutive frames of a video sequence. The detector is trained (using AdaBoost) to take advantage of both moti ..."
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Cited by 569 (3 self)
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This paper describes a pedestrian detection system that integrates image intensity information with motion information. We use a detection style algorithm that scans a detector over two consecutive frames of a video sequence. The detector is trained (using AdaBoost) to take advantage of both motion and appearance information to detect a walking person. Past approaches have built detectors based on motion information or detectors based on appearance information, but ours is the first to combine both sources of information in a single detector. The implementation described runs at about 4 frames/second, detects pedestrians at very small scales (as small as 20x15 pixels), and has a very low false positive rate
Factor Graphs and the SumProduct Algorithm
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 1998
"... A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple c ..."
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Cited by 1787 (72 self)
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A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Bayesian networks, Markov random fields, and Tanner graphs. Following one simple computational rule, the sumproduct algorithm operates in factor graphs to computeeither exactly or approximatelyvarious marginal functions by distributed messagepassing in the graph. A wide variety of algorithms developed in artificial intelligence, signal processing, and digital communications can be derived as specific instances of the sumproduct algorithm, including the forward/backward algorithm, the Viterbi algorithm, the iterative "turbo" decoding algorithm, Pearl's belief propagation algorithm for Bayesian networks, the Kalman filter, and certain fast Fourier transform algorithms.
Is it an Agent, or just a Program?: A Taxonomy for Autonomous Agents
 In Intelligent Agents III
, 1997
"... The advent of software agents gave rise to much discussion of just what such an agent is, and of how they differ from programs in general. Here we propose a formal definition of an autonomous agent which clearly distinguishes a software agent from just any program. We also offer the beginnings of a ..."
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Cited by 770 (49 self)
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The advent of software agents gave rise to much discussion of just what such an agent is, and of how they differ from programs in general. Here we propose a formal definition of an autonomous agent which clearly distinguishes a software agent from just any program. We also offer the beginnings of a natural kinds taxonomy of autonomous agents, and discuss possibilities for further classification. Finally, we discuss subagents and multiagent systems.
PseudoRandom Generation from OneWay Functions
 PROC. 20TH STOC
, 1988
"... Pseudorandom generators are fundamental to many theoretical and applied aspects of computing. We show howto construct a pseudorandom generator from any oneway function. Since it is easy to construct a oneway function from a pseudorandom generator, this result shows that there is a pseudorandom gene ..."
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Cited by 887 (22 self)
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Pseudorandom generators are fundamental to many theoretical and applied aspects of computing. We show howto construct a pseudorandom generator from any oneway function. Since it is easy to construct a oneway function from a pseudorandom generator, this result shows that there is a pseudorandom generator iff there is a oneway function.
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