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25,562
LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
- ACM Trans. Math. Software
, 1982
"... An iterative method is given for solving Ax ~ffi b and minU Ax- b 112, where the matrix A is large and sparse. The method is based on the bidiagonalization procedure of Golub and Kahan. It is analytically equivalent to the standard method of conjugate gradients, but possesses more favorable numerica ..."
Abstract
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Cited by 653 (21 self)
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numerical properties. Reliable stopping criteria are derived, along with estimates of standard errors for x and the condition number of A. These are used in the FORTRAN implementation of the method, subroutine LSQR. Numerical tests are described comparing I~QR with several other conjugate
A direct approach to false discovery rates
, 2002
"... Summary. Multiple-hypothesis testing involves guarding against much more complicated errors than single-hypothesis testing. Whereas we typically control the type I error rate for a single-hypothesis test, a compound error rate is controlled for multiple-hypothesis tests. For example, controlling the ..."
Abstract
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Cited by 775 (14 self)
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Summary. Multiple-hypothesis testing involves guarding against much more complicated errors than single-hypothesis testing. Whereas we typically control the type I error rate for a single-hypothesis test, a compound error rate is controlled for multiple-hypothesis tests. For example, controlling
Do Better Schools Matter? Parental Valuation of Elementary Education
- QUARTERLY JOURNAL OF ECONOMICS
, 1999
"... The evaluation of numerous school reforms requires an understanding of the value of better schools. Given the difficulty of calculating the relationship between school quality and student outcomes, I turn to another method and use house prices to infer the value parents place on school quality. I lo ..."
Abstract
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Cited by 500 (3 self)
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The evaluation of numerous school reforms requires an understanding of the value of better schools. Given the difficulty of calculating the relationship between school quality and student outcomes, I turn to another method and use house prices to infer the value parents place on school quality. I
Bagging predictors
, 1996
"... Bagging predictors is a method for generating multiple versions of a predictor and using these to get an aggregated predictor. The aggregation averages over the versions when predicting a numerical outcome and does a plurality vote when predicting a class. The multiple versions are formed by making ..."
Abstract
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Cited by 3650 (1 self)
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Bagging predictors is a method for generating multiple versions of a predictor and using these to get an aggregated predictor. The aggregation averages over the versions when predicting a numerical outcome and does a plurality vote when predicting a class. The multiple versions are formed
Xen and the art of virtualization
- IN SOSP
, 2003
"... Numerous systems have been designed which use virtualization to subdivide the ample resources of a modern computer. Some require specialized hardware, or cannot support commodity operating systems. Some target 100 % binary compatibility at the expense of performance. Others sacrifice security or fun ..."
Abstract
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Cited by 2010 (35 self)
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Numerous systems have been designed which use virtualization to subdivide the ample resources of a modern computer. Some require specialized hardware, or cannot support commodity operating systems. Some target 100 % binary compatibility at the expense of performance. Others sacrifice security
Loopy belief propagation for approximate inference: An empirical study. In:
- Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract
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Cited by 676 (15 self)
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the convergence the more exact the approximation. • If the hidden nodes are binary, then thresholding the loopy beliefs is guaranteed to give the most probable assignment, even though the numerical value of the beliefs may be incorrect. This result only holds for nodes in the loop. In the max-product (or "
An Efficient Solution to the Five-Point Relative Pose Problem
, 2004
"... An efficient algorithmic solution to the classical five-point relative pose problem is presented. The problem is to find the possible solutions for relative camera pose between two calibrated views given five corresponding points. The algorithm consists of computing the coefficients of a tenth degre ..."
Abstract
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Cited by 484 (13 self)
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degree polynomial in closed form and subsequently finding its roots. It is the first algorithm well suited for numerical implementation that also corresponds to the inherent complexity of the problem. We investigate the numerical precision of the algorithm. We also study its performance under noise
Self-Testing/Correcting with Applications to Numerical Problems
, 1990
"... Suppose someone gives us an extremely fast program P that we can call as a black box to compute a function f . Should we trust that P works correctly? A self-testing/correcting pair allows us to: (1) estimate the probability that P (x) 6= f(x) when x is randomly chosen; (2) on any input x, compute ..."
Abstract
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Cited by 361 (27 self)
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Suppose someone gives us an extremely fast program P that we can call as a black box to compute a function f . Should we trust that P works correctly? A self-testing/correcting pair allows us to: (1) estimate the probability that P (x) 6= f(x) when x is randomly chosen; (2) on any input x, compute
Results 1 - 10
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25,562
