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23,958
An online recruitment system for economic experiments
 IN
, 2004
"... In this paper we introduce the Online Recruitment System for Economic Experiments (ORSEE). With this software experimenters have a free, convenient and very powerful tool to organize their experiments and sessions in a standardized way. Additionally, ORSEE provides subject pool statistics, a laborat ..."
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Cited by 611 (7 self)
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In this paper we introduce the Online Recruitment System for Economic Experiments (ORSEE). With this software experimenters have a free, convenient and very powerful tool to organize their experiments and sessions in a standardized way. Additionally, ORSEE provides subject pool statistics, a
Assessing agreement on classification tasks: the kappa statistic
 Computational Linguistics
, 1996
"... Currently, computational linguists and cognitive scientists working in the area of discourse and dialogue argue that their subjective judgments are reliable using several different statistics, none of which are easily interpretable or comparable to each other. Meanwhile, researchers in content analy ..."
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Cited by 846 (9 self)
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Currently, computational linguists and cognitive scientists working in the area of discourse and dialogue argue that their subjective judgments are reliable using several different statistics, none of which are easily interpretable or comparable to each other. Meanwhile, researchers in content
Semantic similarity based on corpus statistics and lexical taxonomy
 Proc of 10th International Conference on Research in Computational Linguistics, ROCLING’97
, 1997
"... This paper presents a new approach for measuring semantic similarity/distance between words and concepts. It combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better quantifie ..."
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Cited by 873 (0 self)
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This paper presents a new approach for measuring semantic similarity/distance between words and concepts. It combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better
The Dantzig selector: statistical estimation when p is much larger than n
, 2005
"... In many important statistical applications, the number of variables or parameters p is much larger than the number of observations n. Suppose then that we have observations y = Ax + z, where x ∈ R p is a parameter vector of interest, A is a data matrix with possibly far fewer rows than columns, n ≪ ..."
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Cited by 879 (14 self)
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In many important statistical applications, the number of variables or parameters p is much larger than the number of observations n. Suppose then that we have observations y = Ax + z, where x ∈ R p is a parameter vector of interest, A is a data matrix with possibly far fewer rows than columns, n
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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sample variances towards a pooled estimate, resulting in far more stable inference when the number of arrays is small. The use of moderated tstatistics has the advantage over the posterior odds that the number of hyperparameters which need to estimated is reduced; in particular, knowledge of the non
MACROECONOMICS AND REALITY
 ECONOMETRICA
, 1980
"... Existing strategies for econometric analysis related to macroeconomics are subject to a number of serious objections, some recently formulated, some old. These objections are summarized in this paper, and it is argued that taken together they make it unlikely that macroeconomic models are in fact ov ..."
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Cited by 805 (1 self)
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Existing strategies for econometric analysis related to macroeconomics are subject to a number of serious objections, some recently formulated, some old. These objections are summarized in this paper, and it is argued that taken together they make it unlikely that macroeconomic models are in fact
An intrusiondetection model
 IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
, 1987
"... A model of a realtime intrusiondetection expert system capable of detecting breakins, penetrations, and other forms of computer abuse is described. The model is based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns of sy ..."
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Cited by 639 (0 self)
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of system usage. The model includes profiles for representing the behavior of subjects with respect to objects in terms of metrics and statistical models, and rules for acquiring knowledge about this behavior from audit records and for detecting anomalous behavior. The model is independent of any particular
Stochastic Perturbation Theory
, 1988
"... . In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a firstorder perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating the variatio ..."
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Cited by 907 (36 self)
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. In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a firstorder perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating
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
Unsupervised texture segmentation using Gabor filters
 Pattern Recognition
"... We presenf a texture segmentation algorithm inspired by the multichannel filtering theory for visual information processing in the early stages of human visual system. The channels are characterized by a bank of Gabor filters that nearly uniformly covers the spatialfrequency domain. We propose a s ..."
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Cited by 616 (20 self)
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systematic filter selection scheme which is based on reconstruction of the input image from the filtered images. Texture features are obtained by subjecting each (selected) filtered image to a nonlinear transformation and computing a measure of “energy ” in a window around each pixel. An unsupervised square
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