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Localitysensitive hashing scheme based on pstable distributions
 In SCG ’04: Proceedings of the twentieth annual symposium on Computational geometry
, 2004
"... inÇÐÓ�Ò We present a novel LocalitySensitive Hashing scheme for the Approximate Nearest Neighbor Problem underÐÔnorm, based onÔstable distributions. Our scheme improves the running time of the earlier algorithm for the case of theÐnorm. It also yields the first known provably efficient approximate ..."
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Cited by 513 (10 self)
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inÇÐÓ�Ò We present a novel LocalitySensitive Hashing scheme for the Approximate Nearest Neighbor Problem underÐÔnorm, based onÔstable distributions. Our scheme improves the running time of the earlier algorithm for the case of theÐnorm. It also yields the first known provably efficient approximate
STABLE DISTRIBUTIONS
"... Abstract. We give some explicit calculations for stable distributions and convergence to them, mainly based on less explicit results in Feller [3]. The main purpose is to provide ourselves with easy reference to explicit formulas and examples. (There are probably no new results.) 1. ..."
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Cited by 1 (1 self)
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Abstract. We give some explicit calculations for stable distributions and convergence to them, mainly based on less explicit results in Feller [3]. The main purpose is to provide ourselves with easy reference to explicit formulas and examples. (There are probably no new results.) 1.
Stable Distributions
"... Abstract—This paper presents two new properties of BGP routes. First, it shows that the frequency of autonomous systems (ASs) appearing in path vectors follow a PowerLaw relationship. Secondly, it shows that path lengths can be characterized accurately by stable distributions. The main implication ..."
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Abstract—This paper presents two new properties of BGP routes. First, it shows that the frequency of autonomous systems (ASs) appearing in path vectors follow a PowerLaw relationship. Secondly, it shows that path lengths can be characterized accurately by stable distributions. The main
Stable Distributions, Pseudorandom Generators, Embeddings and Data Stream Computation
, 2000
"... In this paper we show several results obtained by combining the use of stable distributions with pseudorandom generators for bounded space. In particular: ffl we show how to maintain (using only O(log n=ffl 2 ) words of storage) a sketch C(p) of a point p 2 l n 1 under dynamic updates of its coo ..."
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Cited by 325 (15 self)
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In this paper we show several results obtained by combining the use of stable distributions with pseudorandom generators for bounded space. In particular: ffl we show how to maintain (using only O(log n=ffl 2 ) words of storage) a sketch C(p) of a point p 2 l n 1 under dynamic updates of its
Estimation of Parameters of Stable Distributions
, 2006
"... In this paper, we propose a method based on GMM (the generalized method of moments) to estimate the parameters of stable distributions with 0 < α < 2. We don’t assume symmetry for stable distributions. ..."
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In this paper, we propose a method based on GMM (the generalized method of moments) to estimate the parameters of stable distributions with 0 < α < 2. We don’t assume symmetry for stable distributions.
StableDistribution Stable Distribution Function Description
, 2014
"... A collection and description of functions to compute density, distribution and quantile function and to generate random variates of the stable distribution. The four functions are: [dpqr]stable the (skewed) stable distribution. Usage dstable(x, alpha, beta, gamma = 1, delta = 0, pm = 0, log = FALSE, ..."
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A collection and description of functions to compute density, distribution and quantile function and to generate random variates of the stable distribution. The four functions are: [dpqr]stable the (skewed) stable distribution. Usage dstable(x, alpha, beta, gamma = 1, delta = 0, pm = 0, log = FALSE
The Estimation of Stable Distribution Parameters
 Proc. of IEEE SP Workshop on HigherOrder Statistics
, 1997
"... This paper concerns the estimation of the parameters that describe a stable distribution. Stable distributions are characterised by four parameters which can be estimated using a number of methods and although approximate maximum likelihood estimation (MLE) techniques do exist, they are computationa ..."
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Cited by 4 (0 self)
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This paper concerns the estimation of the parameters that describe a stable distribution. Stable distributions are characterised by four parameters which can be estimated using a number of methods and although approximate maximum likelihood estimation (MLE) techniques do exist
Distributed Snapshots: Determining Global States of Distributed Systems
 ACM TRANSACTIONS ON COMPUTER SYSTEMS
, 1985
"... This paper presents an algorithm by which a process in a distributed system determines a global state of the system during a computation. Many problems in distributed systems can be cast in terms of the problem of detecting global states. For instance, the global state detection algorithm helps to s ..."
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Cited by 1215 (6 self)
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This paper presents an algorithm by which a process in a distributed system determines a global state of the system during a computation. Many problems in distributed systems can be cast in terms of the problem of detecting global states. For instance, the global state detection algorithm helps
Stable Distribution Function Description
, 2013
"... A collection and description of functions to compute density, distribution and quantile function and to generate random variates of the stable distribution. The four functions are: [dpqr]stable the (skewed) stable distribution. Usage dstable(x, alpha, beta, gamma = 1, delta = 0, pm = 0, log = FALSE, ..."
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A collection and description of functions to compute density, distribution and quantile function and to generate random variates of the stable distribution. The four functions are: [dpqr]stable the (skewed) stable distribution. Usage dstable(x, alpha, beta, gamma = 1, delta = 0, pm = 0, log = FALSE
Results 1  10
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1,213,508