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The Complexity of Computing Medians of Relations
, 1998
"... Let N be a finite set and R be the set of all binary relations on N . Consider R endowed with a metric d, the symmetric difference distance. For a given mtuple = (R 1 ; : : : ; Rm ) 2 R m , a relation R 2 R that minimizes the function P m k=1 d(R k ; R) is called a median relation of . In the socia ..."
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Cited by 22 (0 self)
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of preferences, clustering of similar objects, ranking of teams, etc.). In this paper we analyse the computational complexity of all such problems in which the median is required to satisfy one or more of the properties: reexitivity, symmetry, antisymmetry, transitivity and completeness. We prove that whenever
Average Parameterization and Partial Kernelization for Computing Medians
 PROC. 9TH LATIN
, 2010
"... We propose an effective polynomialtime preprocessing strategy for intractable median problems. Developing a new methodological framework, we show that if the input instances of generally intractable problems exhibit a sufficiently high degree of similarity between each other on average, then there ..."
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Cited by 13 (9 self)
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We propose an effective polynomialtime preprocessing strategy for intractable median problems. Developing a new methodological framework, we show that if the input instances of generally intractable problems exhibit a sufficiently high degree of similarity between each other on average
COMPUTING MEDIAN UNBIASED ESTIMATES IN MACROECONOmTRIC MODELS
"... A stochastic simulation procedure is proposed in this papa for obtaining median unbiased (Mu) estimates in macroeconometric models. MU estimates are computed for lagged dependent variable (LDV) coefficients in 18 equations of a macroeconometric model. The 2SLS bias for a coefficient, defined as the ..."
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Cited by 3 (0 self)
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A stochastic simulation procedure is proposed in this papa for obtaining median unbiased (Mu) estimates in macroeconometric models. MU estimates are computed for lagged dependent variable (LDV) coefficients in 18 equations of a macroeconometric model. The 2SLS bias for a coefficient, defined
Novel Algorithms for Computing Medians and Other Quantiles of DiskResident Data
"... In data warehousing applications, numerous OLAP queries involve the processing of holistic operations such as computing the "top N", median, etc. Efficient implementations of these operations are hard to come by. Several algorithms have been proposed in the literature that estimate various ..."
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In data warehousing applications, numerous OLAP queries involve the processing of holistic operations such as computing the "top N", median, etc. Efficient implementations of these operations are hard to come by. Several algorithms have been proposed in the literature that estimate
1 Novel Algorithms for Computing Medians and Other Quantiles of DiskResident Data
"... Abstract. In data warehousing applications, numerous OLAP queries involve the processing of holistic operations such as computing the "top N", median, etc. Efficient implementations of these operations are hard to come by. Several algorithms have been proposed in the literature that estima ..."
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Abstract. In data warehousing applications, numerous OLAP queries involve the processing of holistic operations such as computing the "top N", median, etc. Efficient implementations of these operations are hard to come by. Several algorithms have been proposed in the literature
Escape analysis for Java
 OOPSLA
, 1999
"... This paper presents a simple and efficient data flow algorithm for escape analysis of objects in Java programs to determine (i) if an object can be allocated on the stack; (ii) if an object is accessed only by a single thread duriing its lifetime, so that synchronization operations on that object ca ..."
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Cited by 300 (12 self)
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be used effectively in different calling contexts. We present an interprocedural algorithm that uses the above property to efficiently compute the connection graph and identify the nonescaping objects for methods and threads. The experimental results, from a prototype implementation of our framework
Parameter Estimation Techniques: A Tutorial with Application to Conic Fitting
, 1995
"... Almost all problems in computer vision are related in one form or another to the problem of estimating parameters from noisy data. In this tutorial, we present what is probably the most commonly used techniques for parameter estimation. These include linear leastsquares (pseudoinverse and eigen a ..."
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Cited by 278 (8 self)
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Almost all problems in computer vision are related in one form or another to the problem of estimating parameters from noisy data. In this tutorial, we present what is probably the most commonly used techniques for parameter estimation. These include linear leastsquares (pseudoinverse and eigen
Linear time bounds for median computations
, 1971
"... New upper and lower bounds are presented for the maximum number of comparisons • f(i,n), required to select the ith largest of n numbers. An upper bound is found, by an analysis of a new selection algorithm, to be a linear function of n: f(i,n) ~ 103n/18 < 5.73n, for i < i < n. A lower bo ..."
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Cited by 19 (0 self)
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bound is shown deductively to be: f(i,n)> n+ min(i,ni+l) + [log2(n)] 4, for 2 < i < ni, or, for the case of computing medians: f([n/2],n)>3n/23
Results 1  10
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2,234