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88,013
A kernel statistical test of independence
, 2008
"... Although kernel measures of independence have been widely applied in machine learning (notably in kernel ICA), there is as yet no method to determine whether they have detected statistically significant dependence. We provide a novel test of the independence hypothesis for one particular kernel inde ..."
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Cited by 98 (50 self)
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Although kernel measures of independence have been widely applied in machine learning (notably in kernel ICA), there is as yet no method to determine whether they have detected statistically significant dependence. We provide a novel test of the independence hypothesis for one particular kernel
Kernel independent component analysis
 Journal of Machine Learning Research
, 2002
"... We present a class of algorithms for independent component analysis (ICA) which use contrast functions based on canonical correlations in a reproducing kernel Hilbert space. On the one hand, we show that our contrast functions are related to mutual information and have desirable mathematical propert ..."
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Cited by 464 (24 self)
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We present a class of algorithms for independent component analysis (ICA) which use contrast functions based on canonical correlations in a reproducing kernel Hilbert space. On the one hand, we show that our contrast functions are related to mutual information and have desirable mathematical
High confidence visual recognition of persons by a test of statistical independence
 IEEE TRANS. ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1993
"... A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence. The most unique phenotypic feature visible in a person’s face is the detailed texture of each eye’s iris: An estimate of its statistical complexity in a sample of the ..."
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Cited by 621 (8 self)
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A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence. The most unique phenotypic feature visible in a person’s face is the detailed texture of each eye’s iris: An estimate of its statistical complexity in a sample
A new scale of social desirability independent of psychopathology
 Journal of Consulting Psychology
, 1960
"... It has long been recognized that personality test scores are influenced by nontestrelevant response determinants. Wiggins and Rumrill (1959) distinguish three approaches to this problem. Briefly, interest in the problem of response distortion has been concerned with attempts at statistical correct ..."
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Cited by 695 (1 self)
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It has long been recognized that personality test scores are influenced by nontestrelevant response determinants. Wiggins and Rumrill (1959) distinguish three approaches to this problem. Briefly, interest in the problem of response distortion has been concerned with attempts at statistical
Survey on Independent Component Analysis
 NEURAL COMPUTING SURVEYS
, 1999
"... A common problem encountered in such disciplines as statistics, data analysis, signal processing, and neural network research, is nding a suitable representation of multivariate data. For computational and conceptual simplicity, such a representation is often sought as a linear transformation of the ..."
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Cited by 2309 (104 self)
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A common problem encountered in such disciplines as statistics, data analysis, signal processing, and neural network research, is nding a suitable representation of multivariate data. For computational and conceptual simplicity, such a representation is often sought as a linear transformation
Local features and kernels for classification of texture and object categories: a comprehensive study
 International Journal of Computer Vision
, 2007
"... Recently, methods based on local image features have shown promise for texture and object recognition tasks. This paper presents a largescale evaluation of an approach that represents images as distributions (signatures or histograms) of features extracted from a sparse set of keypoint locations an ..."
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Cited by 653 (34 self)
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and learns a Support Vector Machine classifier with kernels based on two effective measures for comparing distributions, the Earth Mover’s Distance and the χ 2 distance. We first evaluate the performance of our approach with different keypoint detectors and descriptors, as well as different kernels
On the algorithmic implementation of multiclass kernelbased vector machines
 Journal of Machine Learning Research
"... In this paper we describe the algorithmic implementation of multiclass kernelbased vector machines. Our starting point is a generalized notion of the margin to multiclass problems. Using this notion we cast multiclass categorization problems as a constrained optimization problem with a quadratic ob ..."
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Cited by 559 (13 self)
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In this paper we describe the algorithmic implementation of multiclass kernelbased vector machines. Our starting point is a generalized notion of the margin to multiclass problems. Using this notion we cast multiclass categorization problems as a constrained optimization problem with a quadratic
Statistical Analysis of Cointegrated Vectors
 Journal of Economic Dynamics and Control
, 1988
"... We consider a nonstationary vector autoregressive process which is integrated of order 1, and generated by i.i.d. Gaussian errors. We then derive the maximum likelihood estimator of the space of cointegration vectors and the likelihood ratio test of the hypothesis that it has a given number of dimen ..."
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Cited by 2749 (12 self)
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of dimensions. Further we test linear hypotheses about the cointegration vectors. The asymptotic distribution of these test statistics are found and the first is described by a natural multivariate version of the usual test for unit root in an autoregressive process, and the other is a x2 test. 1.
A Bayesian Framework for the Analysis of Microarray Expression Data: Regularized tTest and Statistical Inferences of Gene Changes
 Bioinformatics
, 2001
"... Motivation: DNA microarrays are now capable of providing genomewide patterns of gene expression across many different conditions. The first level of analysis of these patterns requires determining whether observed differences in expression are significant or not. Current methods are unsatisfactory ..."
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Cited by 491 (6 self)
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due to the lack of a systematic framework that can accommodate noise, variability, and low replication often typical of microarray data. Results: We develop a Bayesian probabilistic framework for microarray data analysis. At the simplest level, we model logexpression values by independent normal
A statistical interpretation of term specificity and its application in retrieval
 Journal of Documentation
, 1972
"... Abstract: The exhaustivity of document descriptions and the specificity of index terms are usually regarded as independent. It is suggested that specificity should be interpreted statistically, as a function of term use rather than of term meaning. The effects on retrieval of variations in term spec ..."
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Cited by 589 (3 self)
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Abstract: The exhaustivity of document descriptions and the specificity of index terms are usually regarded as independent. It is suggested that specificity should be interpreted statistically, as a function of term use rather than of term meaning. The effects on retrieval of variations in term
Results 1  10
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88,013