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588
Linear Shrinkage
"... This test covers the determination of the linear shrinkage of a disturbed soil sample. It is a tedious and expensive test that is done only on soils (other than sands) when the dispersion percentage is>50 or volume expansion tests fail to saturate or shrink. This test is performed on dispersive s ..."
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This test covers the determination of the linear shrinkage of a disturbed soil sample. It is a tedious and expensive test that is done only on soils (other than sands) when the dispersion percentage is>50 or volume expansion tests fail to saturate or shrink. This test is performed on dispersive
Locally Computable UOWHF with Linear Shrinkage ∗
"... We study the problem of constructing locally computable Universal OneWay Hash Functions (UOWHFs) H: {0, 1} n → {0, 1} m. A construction with constant output locality, where every bit of the output depends only on a constant number of bits of the input, was established by [Applebaum, Ishai, and Kush ..."
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Cited by 1 (1 self)
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, and Kushilevitz, SICOMP 2006]. However, this construction suffers from two limitations: (1) It can only achieve a sublinear shrinkage of n − m = n 1−ɛ; and (2) It has a superconstant input locality, i.e., some inputs influence a large superconstant number of outputs. This leaves open the question of realizing
Regression Shrinkage and Selection Via the Lasso
 JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B
, 1994
"... We propose a new method for estimation in linear models. The "lasso" minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to produce some coefficients that are exactl ..."
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Cited by 4212 (49 self)
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We propose a new method for estimation in linear models. The "lasso" minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to produce some coefficients
Ideal spatial adaptation by wavelet shrinkage
 Biometrika
, 1994
"... With ideal spatial adaptation, an oracle furnishes information about how best to adapt a spatially variable estimator, whether piecewise constant, piecewise polynomial, variable knot spline, or variable bandwidth kernel, to the unknown function. Estimation with the aid of an oracle o ers dramatic ad ..."
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Cited by 1269 (5 self)
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advantages over traditional linear estimation by nonadaptive kernels � however, it is a priori unclear whether such performance can be obtained by a procedure relying on the data alone. We describe a new principle for spatiallyadaptive estimation: selective wavelet reconstruction. Weshowthatvariableknot
A fast iterative shrinkagethresholding algorithm with application to . . .
, 2009
"... We consider the class of Iterative ShrinkageThresholding Algorithms (ISTA) for solving linear inverse problems arising in signal/image processing. This class of methods is attractive due to its simplicity, however, they are also known to converge quite slowly. In this paper we present a Fast Iterat ..."
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Cited by 1058 (9 self)
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We consider the class of Iterative ShrinkageThresholding Algorithms (ISTA) for solving linear inverse problems arising in signal/image processing. This class of methods is attractive due to its simplicity, however, they are also known to converge quite slowly. In this paper we present a Fast
NonLinear Shrinkage Estimation with Complex Daubechies Wavelets
 PROCEEDINGS OF SPIE, WAVELET APPLICATIONS IN SIGNAL AND IMAGE PROCESSING V
, 1997
"... One of the main advantages of the discrete wavelet representation is the nearoptimal estimation of signals corrupted with noise. After the seminal work of De Vore and Lucier (1992) and Donoho and Johnstone (1995), new techniques for choosing appropriate threshold and/or shrinkage functions have rec ..."
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Cited by 6 (0 self)
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One of the main advantages of the discrete wavelet representation is the nearoptimal estimation of signals corrupted with noise. After the seminal work of De Vore and Lucier (1992) and Donoho and Johnstone (1995), new techniques for choosing appropriate threshold and/or shrinkage functions have
SCOPE Definition METHOD A4 THE DETERMINATION OF THE LINEAR SHRINKAGE OF SOILS
"... This method covers the determination of the linear shrinkage of soil when it is dried from a moisture content equivalent to the liquid limit to the ovendry state. The linear shrinkage of a soil for the moisture content equivalent to the liquid limit, is the decrease in one dimension, expressed as a ..."
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This method covers the determination of the linear shrinkage of soil when it is dried from a moisture content equivalent to the liquid limit to the ovendry state. The linear shrinkage of a soil for the moisture content equivalent to the liquid limit, is the decrease in one dimension, expressed
On the Strong Convergence of the Optimal Linear Shrinkage Estimator for Large Dimensional Covariance Matrix∗
"... In this work we construct an optimal linear shrinkage estimator for the covariance matrix in high dimensions. The recent results from the random matrix theory allow us to find the asymptotic deterministic equivalents of the optimal shrinkage intensities and estimate them consistently. The develope ..."
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In this work we construct an optimal linear shrinkage estimator for the covariance matrix in high dimensions. The recent results from the random matrix theory allow us to find the asymptotic deterministic equivalents of the optimal shrinkage intensities and estimate them consistently
Linear models and empirical bayes methods for assessing differential expression in microarray experiments.
 Stat. Appl. Genet. Mol. Biol.
, 2004
"... Abstract The problem of identifying differentially expressed genes in designed microarray experiments is considered. Lonnstedt and Speed (2002) derived an expression for the posterior odds of differential expression in a replicated twocolor experiment using a simple hierarchical parametric model. ..."
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Cited by 1321 (24 self)
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. The purpose of this paper is to develop the hierarchical model of Lonnstedt and Speed (2002) into a practical approach for general microarray experiments with arbitrary numbers of treatments and RNA samples. The model is reset in the context of general linear models with arbitrary coefficients and contrasts
Compensation of NonLinear Shrinkage of Polymer Materials in Selective Laser Sintering
"... Inaccuracies in the selective laser sintering (SLS) process using polymer materials are typically caused by inhomogeneous shrinkage due to inhomogeneous temperature distribution in the powder bed of the SLS machine. These shrinking effects lead to stress in the sintered parts, causing the part to di ..."
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Cited by 2 (0 self)
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Inaccuracies in the selective laser sintering (SLS) process using polymer materials are typically caused by inhomogeneous shrinkage due to inhomogeneous temperature distribution in the powder bed of the SLS machine. These shrinking effects lead to stress in the sintered parts, causing the part
Results 1  10
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588