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CE: Basic principles of ROC analysis
 Seminars in Nuclear Medicine
, 1978
"... The l imitations of diagnostic "accuracy " as a measure of decision performance require introduction of the concepts of the "sensit iv ity " and "specif ic i ty " of a diagnostic test, These measures and the related indices, "true positive fraction " and &quo ..."
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Cited by 376 (0 self)
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; and "false positive fract ion, " are more meaningful than "'accuracy, " yet do not provide a unique description of diagnostic performance because they depend on the arbitrary selection of a decision threshold. The receiver operating characteristic (ROC) curve is shown to be a
Practical Threshold Signatures
, 1999
"... We present an RSA threshold signature scheme. The scheme enjoys the following properties: 1. it is unforgeable and robust in the random oracle model, assuming the RSA problem is hard ..."
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Cited by 240 (2 self)
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We present an RSA threshold signature scheme. The scheme enjoys the following properties: 1. it is unforgeable and robust in the random oracle model, assuming the RSA problem is hard
Hierarchical classification of Web content
, 2000
"... sdumais @ microsoft.com This paper explores the use of hierarchical structure for classifying a large, heterogeneous collection of web content. The hierarchical structure is initially used to train different secondlevel classifiers. In the hierarchical case, a model is learned to distinguish a seco ..."
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Cited by 329 (4 self)
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a threshold at the top level. We use support vector machine (SVM) classifiers, which have been shown to be efficient and effective for classification, but not previously explored in the context of hierarchical classification. We found small advantages in accuracy for hierarchical models over flat
Cooperative sensing among cognitive radios
 In Proc. of the IEEE International Conference on Communications (ICC
, 2006
"... Abstract — Cognitive Radios have been advanced as a technology for the opportunistic use of underutilized spectrum since they are able to sense the spectrum and use frequency bands if no Primary user is detected. However, the required sensitivity is very demanding since any individual Radio might f ..."
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Cited by 289 (15 self)
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. Even a few cooperating users (∼1020) facing independent fades are enough to achieve practical threshold levels by drastically reducing the individual detection requirements. Hard decisions perform almost as well as soft decisions in achieving these gains. Shadowing correlation limits these gains
Wavelet Threshold Estimators for Data With Correlated Noise
, 1994
"... Wavelet threshold estimators for data with stationary correlated noise are constructed by the following prescription. First, form the discrete wavelet transform of the data points. Next, apply a leveldependent soft threshold to the individual coefficients, allowing the thresholds to depend on the l ..."
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Cited by 240 (15 self)
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Wavelet threshold estimators for data with stationary correlated noise are constructed by the following prescription. First, form the discrete wavelet transform of the data points. Next, apply a leveldependent soft threshold to the individual coefficients, allowing the thresholds to depend
Spectral hashing
, 2009
"... Semantic hashing [1] seeks compact binary codes of datapoints so that the Hamming distance between codewords correlates with semantic similarity. In this paper, we show that the problem of finding a best code for a given dataset is closely related to the problem of graph partitioning and can be sho ..."
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Cited by 284 (4 self)
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be shown to be NP hard. By relaxing the original problem, we obtain a spectral method whose solutions are simply a subset of thresholded eigenvectors of the graph Laplacian. By utilizing recent results on convergence of graph Laplacian eigenvectors to the LaplaceBeltrami eigenfunctions of manifolds, we
A Static Analyzer for Large SafetyCritical Software
, 2003
"... We show that abstract interpretationbased static program analysis can be made e#cient and precise enough to formally verify a class of properties for a family of large programs with few or no false alarms. This is achieved by refinement of a general purpose static analyzer and later adaptation to p ..."
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Cited by 271 (54 self)
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and adaptation through parametrization, the symbolic manipulation of expressions to improve the precision of abstract transfer functions, ellipsoid, and decision tree abstract domains, all with sound handling of rounding errors in floating point computations, widening strategies (with thresholds, delayed
Sparse solution of underdetermined linear equations by stagewise orthogonal matching pursuit
, 2006
"... Finding the sparsest solution to underdetermined systems of linear equations y = Φx is NPhard in general. We show here that for systems with ‘typical’/‘random ’ Φ, a good approximation to the sparsest solution is obtained by applying a fixed number of standard operations from linear algebra. Our pr ..."
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Cited by 274 (22 self)
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Finding the sparsest solution to underdetermined systems of linear equations y = Φx is NPhard in general. We show here that for systems with ‘typical’/‘random ’ Φ, a good approximation to the sparsest solution is obtained by applying a fixed number of standard operations from linear algebra. Our
Adaptive disk spindown policies for mobile computers
 In Proceedings 2nd USENIX Symp. on Mobile and LocationIndependent Computing
, 1995
"... ABSTRACT: Mobile computers typically spin down their hard disk after a fixed period of inactivity. If this threshold is too long, the disk wastes energy; if it is too short, the delay due to spinning the disk up again frushates the user. Usage patterns change over time, so a single fixed threshold m ..."
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Cited by 237 (7 self)
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ABSTRACT: Mobile computers typically spin down their hard disk after a fixed period of inactivity. If this threshold is too long, the disk wastes energy; if it is too short, the delay due to spinning the disk up again frushates the user. Usage patterns change over time, so a single fixed threshold
The Gambler's Ruin Problem, Genetic Algorithms, and the Sizing of Populations
, 1997
"... This paper presents a model for predicting the convergence quality of genetic algorithms. The model incorporates previous knowledge about decision making in genetic algorithms and the initial supply of building blocks in a novel way. The result is an equation that accurately predicts the quality of ..."
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Cited by 245 (89 self)
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This paper presents a model for predicting the convergence quality of genetic algorithms. The model incorporates previous knowledge about decision making in genetic algorithms and the initial supply of building blocks in a novel way. The result is an equation that accurately predicts the quality
Results 11  20
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8,979