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22,125
An Algorithm for Tracking Multiple Targets
 IEEE Transactions on Automatic Control
, 1979
"... Abstractâ€”An algorithm for tracking multiple targets In a cluttered algorithms. Clustering is the process of dividing the entire environment Is developed. The algorithm Is capable of Initiating tracks, set of targets and measurements into independent groups accounting for false or m[~clngreports, and ..."
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Cited by 596 (0 self)
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Abstractâ€”An algorithm for tracking multiple targets In a cluttered algorithms. Clustering is the process of dividing the entire environment Is developed. The algorithm Is capable of Initiating tracks, set of targets and measurements into independent groups accounting for false or m
Fast Parallel Algorithms for ShortRange Molecular Dynamics
 JOURNAL OF COMPUTATIONAL PHYSICS
, 1995
"... Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of interatomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dyn ..."
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Cited by 653 (7 self)
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. The algorithms are tested on a standard LennardJones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers  the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray YMP and C90 algorithm shows
Dynamic programming algorithm optimization for spoken word recognition
 IEEE TRANSACTIONS ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING
, 1978
"... This paper reports on an optimum dynamic programming (DP) based timenormalization algorithm for spoken word recognition. First, a general principle of timenormalization is given using timewarping function. Then, two timenormalized distance definitions, ded symmetric and asymmetric forms, are der ..."
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Cited by 788 (3 self)
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This paper reports on an optimum dynamic programming (DP) based timenormalization algorithm for spoken word recognition. First, a general principle of timenormalization is given using timewarping function. Then, two timenormalized distance definitions, ded symmetric and asymmetric forms
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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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
An Optimal Algorithm for Approximate Nearest Neighbor Searching in Fixed Dimensions
 ACMSIAM SYMPOSIUM ON DISCRETE ALGORITHMS
, 1994
"... Consider a set S of n data points in real ddimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q 2 R d , the closest point of S to q can be reported quickly. Given any po ..."
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Cited by 984 (32 self)
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Consider a set S of n data points in real ddimensional space, R d , where distances are measured using any Minkowski metric. In nearest neighbor searching we preprocess S into a data structure, so that given any query point q 2 R d , the closest point of S to q can be reported quickly. Given any
Segmentation of brain MR images through a hidden Markov random field model and the expectationmaximization algorithm
 IEEE TRANSACTIONS ON MEDICAL. IMAGING
, 2001
"... The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogrambased model, the FM has an intrinsic limi ..."
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Cited by 639 (15 self)
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that the FM model is a degenerate version of the HMRF model. The advantage of the HMRF model derives from the way in which the spatial information is encoded through the mutual influences of neighboring sites. Although MRF modeling has been employed in MR image segmentation by other researchers, most reported
Improved algorithms for topic distillation in a hyperlinked environment
 In SIGIR Conference on Research and Development in Information Retrieval
, 1998
"... Abstract This paper addresses the problem of topic distillation on the World Wide Web, namely, given a typical user query to find quality documents related to the query topic. Connectivity analysis has been shown to be useful in identifying high quality pages within a topic specific graph of hyperli ..."
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Cited by 471 (8 self)
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of hyperlinked documents. The essence of our approach is to augment a previous connectivity analysis based algorithm with content analysis. We identify three problems with the existing approach and devise algorithms to tackle them. The results of a user evaluation are reported that show an improvement
Signal recovery from random measurements via Orthogonal Matching Pursuit
 IEEE TRANS. INFORM. THEORY
, 2007
"... This technical report demonstrates theoretically and empirically that a greedy algorithm called Orthogonal Matching Pursuit (OMP) can reliably recover a signal with m nonzero entries in dimension d given O(m ln d) random linear measurements of that signal. This is a massive improvement over previous ..."
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Cited by 802 (9 self)
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This technical report demonstrates theoretically and empirically that a greedy algorithm called Orthogonal Matching Pursuit (OMP) can reliably recover a signal with m nonzero entries in dimension d given O(m ln d) random linear measurements of that signal. This is a massive improvement over
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 interframe 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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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 interframe displacement made possible by the factorization approach, the best tracking method turns out to be the one proposed by Lucas and Kanade
A Study of CrossValidation and Bootstrap for Accuracy Estimation and Model Selection
 INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE
, 1995
"... We review accuracy estimation methods and compare the two most common methods: crossvalidation and bootstrap. Recent experimental results on artificial data and theoretical results in restricted settings have shown that for selecting a good classifier from a set of classifiers (model selection), te ..."
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Cited by 1283 (11 self)
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), tenfold crossvalidation may be better than the more expensive leaveoneout crossvalidation. We report on a largescale experiment  over half a million runs of C4.5 and a NaiveBayes algorithm  to estimate the effects of different parameters on these algorithms on realworld datasets. For cross
Results 1  10
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22,125