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Many Random Walks Are Faster Than One
"... We pose a new and intriguing question motivated by distributed computing regarding random walks on graphs: How long does it take for several independent random walks, starting from the same vertex, to cover an entire graph? We study the cover time–the expected time required to visit every node in a ..."
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Cited by 46 (3 self)
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graph at least once–and we show that for a large collection of interesting graphs, running many random walks in parallel yields a speedup in the cover time that is linear in the number of parallel walks. We demonstrate that an exponential speedup is sometimes possible, but that some natural graphs
Many Random Walks Are Faster Than One
, 2006
"... This paper is about searching a graph with a random walk. We show that several random walks running (or walking) in parallel can often search a graph much faster than a single random walk on its own. We measure the cover time, which is the expected amount of time required to visit every node in the ..."
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This paper is about searching a graph with a random walk. We show that several random walks running (or walking) in parallel can often search a graph much faster than a single random walk on its own. We measure the cover time, which is the expected amount of time required to visit every node
LITERATURE REVIEW: Many Random Walks are Faster Than One Some Experimental Results
, 2008
"... A well studied approach to efficiently traversing and exploring and unknown graph is through randomized means. Random walks start at a node of a given graph and can move to an adjacent node chosen at random. In parallel situations it seems natural to extend this technique ask if multiple random walk ..."
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A well studied approach to efficiently traversing and exploring and unknown graph is through randomized means. Random walks start at a node of a given graph and can move to an adjacent node chosen at random. In parallel situations it seems natural to extend this technique ask if multiple random
Randomized Algorithms
, 1995
"... Randomized algorithms, once viewed as a tool in computational number theory, have by now found widespread application. Growth has been fueled by the two major benefits of randomization: simplicity and speed. For many applications a randomized algorithm is the fastest algorithm available, or the simp ..."
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Cited by 2210 (37 self)
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Randomized algorithms, once viewed as a tool in computational number theory, have by now found widespread application. Growth has been fueled by the two major benefits of randomization: simplicity and speed. For many applications a randomized algorithm is the fastest algorithm available
Random walks for image segmentation
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2006
"... Abstract—A novel method is proposed for performing multilabel, interactive image segmentation. Given a small number of pixels with userdefined (or predefined) labels, one can analytically and quickly determine the probability that a random walker starting at each unlabeled pixel will first reach on ..."
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Cited by 385 (21 self)
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Abstract—A novel method is proposed for performing multilabel, interactive image segmentation. Given a small number of pixels with userdefined (or predefined) labels, one can analytically and quickly determine the probability that a random walker starting at each unlabeled pixel will first reach
A Direct Adaptive Method for Faster Backpropagation Learning: The RPROP Algorithm
 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS
, 1993
"... A new learning algorithm for multilayer feedforward networks, RPROP, is proposed. To overcome the inherent disadvantages of pure gradientdescent, RPROP performs a local adaptation of the weightupdates according to the behaviour of the errorfunction. In substantial difference to other adaptive tech ..."
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Cited by 917 (34 self)
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A new learning algorithm for multilayer feedforward networks, RPROP, is proposed. To overcome the inherent disadvantages of pure gradientdescent, RPROP performs a local adaptation of the weightupdates according to the behaviour of the errorfunction. In substantial difference to other adaptive techniques, the effect of the RPROP adaptation process is not blurred by the unforseeable influence of the size of the derivative but only dependent on the temporal behaviour of its sign. This leads to an efficient and transparent adaptation process. The promising capabilities of RPROP are shown in comparison to other wellknown adaptive techniques.
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
Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test
 REVIEW OF FINANCIAL STUDIES
, 1988
"... In this article we test the random walk hypothesis for weekly stock market returns by comparing variance estimators derived from data sampled at different frequencies. The random walk model is strongly rejected for the entire sample period (19621985) and for all subperiod for a variety of aggrega ..."
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Cited by 492 (18 self)
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In this article we test the random walk hypothesis for weekly stock market returns by comparing variance estimators derived from data sampled at different frequencies. The random walk model is strongly rejected for the entire sample period (19621985) and for all subperiod for a variety
Results 1  10
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2,712,011