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556,258
Estimating the Support of a HighDimensional Distribution
, 1999
"... Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We propo ..."
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Cited by 766 (29 self)
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Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We
EEGLAB: an open source toolbox for analysis of singletrial EEG dynamics including independent component analysis
 J. Neurosci. Methods
"... Abstract: We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of singletrial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event i ..."
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Cited by 836 (44 self)
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. Extensive function help and tutorial information are included. A ‘plugin ’ facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available
Gravity with Gravitas: a Solution to the Border Puzzle
, 2001
"... Gravity equations have been widely used to infer trade ow effects of various institutional arrangements. We show that estimated gravity equations do not have a theoretical foundation. This implies both that estimation suffers from omitted variables bias and that comparative statics analysis is unfo ..."
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Cited by 610 (3 self)
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Gravity equations have been widely used to infer trade ow effects of various institutional arrangements. We show that estimated gravity equations do not have a theoretical foundation. This implies both that estimation suffers from omitted variables bias and that comparative statics analysis
Wattch: A Framework for ArchitecturalLevel Power Analysis and Optimizations
 In Proceedings of the 27th Annual International Symposium on Computer Architecture
, 2000
"... Power dissipation and thermal issues are increasingly significant in modern processors. As a result, it is crucial that power/performance tradeoffs be made more visible to chip architects and even compiler writers, in addition to circuit designers. Most existing power analysis tools achieve high ..."
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Cited by 1295 (43 self)
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high accuracy by calculating power estimates for designs only after layout or floorplanning are complete In addition to being available only late in the design process, such tools are often quite slow, which compounds the difficulty of running them for a large space of design possibilities.
Locally weighted learning
 ARTIFICIAL INTELLIGENCE REVIEW
, 1997
"... This paper surveys locally weighted learning, a form of lazy learning and memorybased learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias, ass ..."
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Cited by 594 (53 self)
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This paper surveys locally weighted learning, a form of lazy learning and memorybased learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias
"GrabCut”  interactive foreground extraction using iterated graph cuts
 ACM TRANS. GRAPH
, 2004
"... The problem of efficient, interactive foreground/background segmentation in still images is of great practical importance in image editing. Classical image segmentation tools use either texture (colour) information, e.g. Magic Wand, or edge (contrast) information, e.g. Intelligent Scissors. Recently ..."
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Cited by 1140 (36 self)
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of the iterative algorithm is used to simplify substantially the user interaction needed for a given quality of result. Thirdly, a robust algorithm for “border matting ” has been developed to estimate simultaneously the alphamatte around an object boundary and the colours of foreground pixels. We show
Regularized discriminant analysis
 J. Amer. Statist. Assoc
, 1989
"... Linear and quadratic discriminant analysis are considered in the small sample highdimensional setting. Alternatives to the usual maximum likelihood (plugin) estimates for the covariance matrices are proposed. These alternatives are characterized by two parameters, the values of which are customize ..."
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Cited by 460 (2 self)
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Linear and quadratic discriminant analysis are considered in the small sample highdimensional setting. Alternatives to the usual maximum likelihood (plugin) estimates for the covariance matrices are proposed. These alternatives are characterized by two parameters, the values of which
A simple transmit diversity technique for wireless communications
 IEEE Journal on Selected Areas in Communications
, 1998
"... Abstract — This paper presents a simple twobranch transmit diversity scheme. Using two transmit antennas and one receive antenna the scheme provides the same diversity order as maximalratio receiver combining (MRRC) with one transmit antenna, and two receive antennas. It is also shown that the sch ..."
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Cited by 2084 (0 self)
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processing, baseband processing, diversity, estimation and detection, fade mitigation, maximalratio combining, Rayleigh fading, smart antennas, space block coding, space–time coding, transmit diversity, wireless communications. I.
A LongMemory Property of Stock Market Returns and a New Model
 Journal of Empirical Finance
, 1993
"... A ‘long memory ’ property of stock market returns is investigated in this paper. It is found that not only there is substantially more correlation between absolute returns than returns themselves, but the power transformation of the absolute return lrfl ” also has quite high autocorrelation for lo ..."
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Cited by 606 (21 self)
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based on absolute return can produce this property. A new general class of models is proposed which allows the power 6 of the heteroskedasticity equation to be estimated from the data. 1.
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 886 (35 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
Results 1  10
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556,258