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Results 1 - 10
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7,252
Understanding and using the Implicit Association Test: I. An improved scoring algorithm
- Journal of Personality and Social Psychology
, 2003
"... behavior relations Greenwald et al. Predictive validity of the IAT (Draft of 30 Dec 2008) 2 Abstract (131 words) This review of 122 research reports (184 independent samples, 14,900 subjects), found average r=.274 for prediction of behavioral, judgment, and physiological measures by Implic ..."
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Cited by 632 (94 self)
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sensitive topics, for which impression management may distort self-report responses. For 32 samples with criterion measures involving Black–White interracial behavior, predictive validity of IAT measures significantly exceeded that of self-report measures. Both IAT and self-report measures displayed
for Research Utilizing Multiple Criterion Measures
"... There is a salutary trend in the evalua-tion of an instructional method, treatment, or educational program to employ several criteria. Current lit-erature abounds in studies involving multiple measurements on experimental units. For example, Serwer, Shapiro, and Shapiro (1973) utilized more than 20 ..."
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There is a salutary trend in the evalua-tion of an instructional method, treatment, or educational program to employ several criteria. Current lit-erature abounds in studies involving multiple measurements on experimental units. For example, Serwer, Shapiro, and Shapiro (1973) utilized more than 20
Detection and Tracking of Point Features
- International Journal of Computer Vision
, 1991
"... The factorization method described in this series of reports requires an algorithm to track the motion of features in an image stream. Given the small inter-frame displacement made possible by the factorization approach, the best tracking method turns out to be the one proposed by Lucas and Kanade i ..."
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Cited by 629 (2 self)
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in 1981. The method defines the measure of match between fixed-size feature windows in the past and current frame as the sum of squared intensity differences over the windows. The displacement is then defined as the one that minimizes this sum. For small motions, a linearization of the image intensities
Multimodality Image Registration by Maximization of Mutual Information
- IEEE TRANSACTIONS ON MEDICAL IMAGING
, 1997
"... A new approach to the problem of multimodality medical image registration is proposed, using a basic concept from information theory, mutual information (MI), or relative entropy, as a new matching criterion. The method presented in this paper applies MI to measure the statistical dependence or in ..."
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Cited by 791 (10 self)
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A new approach to the problem of multimodality medical image registration is proposed, using a basic concept from information theory, mutual information (MI), or relative entropy, as a new matching criterion. The method presented in this paper applies MI to measure the statistical dependence
The use of MMR, diversity-based reranking for reordering documents and producing summaries
- In SIGIR
, 1998
"... jadeQcs.cmu.edu Abstract This paper presents a method for combining query-relevance with information-novelty in the context of text retrieval and summarization. The Maximal Marginal Relevance (MMR) criterion strives to reduce redundancy while maintaining query relevance in re-ranking retrieved docum ..."
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Cited by 768 (14 self)
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relevance to the user’s query. In contrast, we motivated the need for “relevant novelty ” as a potentially superior criterion. A first approximation to measuring relevant novelty is to measure relevance and novelty independently and provide a linear combination as the metric. We call the linear combination
Empirical Bayes Analysis of a Microarray Experiment
- Journal of the American Statistical Association
, 2001
"... Microarrays are a novel technology that facilitates the simultaneous measurement of thousands of gene expression levels. A typical microarray experiment can produce millions of data points, raising serious problems of data reduction, and simultaneous inference. We consider one such experiment in whi ..."
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Cited by 492 (20 self)
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Microarrays are a novel technology that facilitates the simultaneous measurement of thousands of gene expression levels. A typical microarray experiment can produce millions of data points, raising serious problems of data reduction, and simultaneous inference. We consider one such experiment
X-means: Extending K-means with Efficient Estimation of the Number of Clusters
- In Proceedings of the 17th International Conf. on Machine Learning
, 2000
"... Despite its popularity for general clustering, K-means suffers three major shortcomings; it scales poorly computationally, the number of clusters K has to be supplied by the user, and the search is prone to local minima. We propose solutions for the first two problems, and a partial remedy for the t ..."
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Cited by 418 (5 self)
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for the third. Building on prior work for algorithmic acceleration that is not based on approximation, we introduce a new algorithm that efficiently, searches the space of cluster locations and number of clusters to optimize the Bayesian Information Criterion (BIC) or the Akaike Information Criterion (AIC
Spectral Efficiency in the Wideband Regime
, 2002
"... The tradeoff of spectral efficiency (b/s/Hz) versus energy -per-information bit is the key measure of channel capacity in the wideband power-limited regime. This paper finds the fundamental bandwidth--power tradeoff of a general class of channels in the wideband regime characterized by low, but nonz ..."
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Cited by 393 (29 self)
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The tradeoff of spectral efficiency (b/s/Hz) versus energy -per-information bit is the key measure of channel capacity in the wideband power-limited regime. This paper finds the fundamental bandwidth--power tradeoff of a general class of channels in the wideband regime characterized by low
Combined Object Categorization and Segmentation With An Implicit Shape Model
- In ECCV workshop on statistical learning in computer vision
, 2004
"... We present a method for object categorization in real-world scenes. Following a common consensus in the field, we do not assume that a figure-ground segmentation is available prior to recognition. However, in contrast to most standard approaches for object class recognition, our approach automatical ..."
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Cited by 406 (10 self)
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result, it also generates a per-pixel confidence measure specifying the area that supports a hypothesis and how much it can be trusted. We use this confidence to derive a natural extension of the approach to handle multiple objects in a scene and resolve ambiguities between overlapping hypotheses with a
Characteristics of Reading Aloud, Word Identification, and Maze Selection as Growth Measures: Relationship between Growth and Criterion Measures
, 2005
"... The purpose of this study was to compare the characteristics of reading aloud, word identification, and maze selection as growth measures with performance on criterion measures. The following research question was addressed: Which weekly progress monitoring measures in reading (reading aloud or maze ..."
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The purpose of this study was to compare the characteristics of reading aloud, word identification, and maze selection as growth measures with performance on criterion measures. The following research question was addressed: Which weekly progress monitoring measures in reading (reading aloud
Results 1 - 10
of
7,252
