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3,384
Adapting to unknown smoothness via wavelet shrinkage
 JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
, 1995
"... We attempt to recover a function of unknown smoothness from noisy, sampled data. We introduce a procedure, SureShrink, which suppresses noise by thresholding the empirical wavelet coefficients. The thresholding is adaptive: a threshold level is assigned to each dyadic resolution level by the princip ..."
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Cited by 1006 (18 self)
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on the choice of mother wavelet. We know from a previous paper by the authors that traditional smoothing methods  kernels, splines, and orthogonal series estimates  even with optimal choices of the smoothing parameter, would be unable to perform
Characterization of Isospectral Graphs Using Graph Invariants and Derived Orthogonal Parameters
 J. Chem. Inf. Comput. Sci. 1998
"... Numerical graph theoretic invariants or topological indices (TIs) and principal components (PCs) derived from TIs have been used in discriminating a set of isospectral graphs. Results show that lower order connectivity and information theoretic TIs suffer from a high degree of redundancy, whereas h ..."
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Cited by 4 (3 self)
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Numerical graph theoretic invariants or topological indices (TIs) and principal components (PCs) derived from TIs have been used in discriminating a set of isospectral graphs. Results show that lower order connectivity and information theoretic TIs suffer from a high degree of redundancy, whereas higher order indices can characterize the graphs reasonably well. On the other hand, PCs derived from the TIs had no redundancy for the set of isospectral graphs studied.
ACCURATE PROCEDURES FOR APPROXIMATE BAYESIAN AND CONDITIONAL INFERENCE WITHOUT THE NEED FOR ORTHOGONAL PARAMETERS BY
"... Approved for public release; distribution unlimited. ..."
Parameter Estimation Techniques: A Tutorial with Application to Conic Fitting
, 1995
"... Almost all problems in computer vision are related in one form or another to the problem of estimating parameters from noisy data. In this tutorial, we present what is probably the most commonly used techniques for parameter estimation. These include linear leastsquares (pseudoinverse and eigen a ..."
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Cited by 278 (8 self)
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Almost all problems in computer vision are related in one form or another to the problem of estimating parameters from noisy data. In this tutorial, we present what is probably the most commonly used techniques for parameter estimation. These include linear leastsquares (pseudoinverse and eigen
Blind separation of speech mixtures via timefrequency masking
 IEEE TRANSACTIONS ON SIGNAL PROCESSING (2002) SUBMITTED
, 2004
"... Binary timefrequency masks are powerful tools for the separation of sources from a single mixture. Perfect demixing via binary timefrequency masks is possible provided the timefrequency representations of the sources do not overlap: a condition we calldisjoint orthogonality. We introduce here t ..."
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Cited by 322 (5 self)
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Binary timefrequency masks are powerful tools for the separation of sources from a single mixture. Perfect demixing via binary timefrequency masks is possible provided the timefrequency representations of the sources do not overlap: a condition we calldisjoint orthogonality. We introduce here
The Michigan Internet AuctionBot: A configurable auction server for human and software agents
 IN PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS, MAY1998
, 1998
"... Market mechanisms, such as auctions, will likely represent a common interaction medium for agents on the Internet. The Michigan Internet AuctionBot is a flexible, scalable, and robust auction server that supports both software and human agents. The server manages many simultaneous auctions by separa ..."
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Cited by 250 (15 self)
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to the general Internet population. Its flexible specification of auctions in terms of orthogonal parameters makes it a useful device for agent researchers exploring the design space of auction mechanisms.
The development and comparison of robust methods for estimating the fundamental matrix
 International Journal of Computer Vision
, 1997
"... Abstract. This paper has two goals. The first is to develop a variety of robust methods for the computation of the Fundamental Matrix, the calibrationfree representation of camera motion. The methods are drawn from the principal categories of robust estimators, viz. case deletion diagnostics, Mest ..."
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Cited by 266 (10 self)
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estimators and random sampling, and the paper develops the theory required to apply them to nonlinear orthogonal regression problems. Although a considerable amount of interest has focussed on the application of robust estimation in computer vision, the relative merits of the many individual methods are unknown
On parameter orthogonality in symmetric and skew models
 Journal of Statistical Planning and Inference
, 2010
"... Orthogonal and partly orthogonal reparametrisations are provided for certain wide and important families of univariate continuous distributions. First, the orthogonality of parameters in locationscale symmetric families is extended to symmetric distributions involving a third parameter. This sets t ..."
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Cited by 8 (2 self)
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Orthogonal and partly orthogonal reparametrisations are provided for certain wide and important families of univariate continuous distributions. First, the orthogonality of parameters in locationscale symmetric families is extended to symmetric distributions involving a third parameter. This sets
Classical orthogonal polynomials: dependence of parameters
, 2000
"... Most of the classical orthogonal polynomials (continuous, discrete and their qanalogues) can be considered as functions of several parameters ci. A systematic study of the variation, infinitesimal and finite, of these polynomials Pn(x; ci) with respect to the parameters ci is proposed. A method to ..."
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Cited by 4 (0 self)
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Most of the classical orthogonal polynomials (continuous, discrete and their qanalogues) can be considered as functions of several parameters ci. A systematic study of the variation, infinitesimal and finite, of these polynomials Pn(x; ci) with respect to the parameters ci is proposed. A method
Printed in Great Britain On the construction of a parameter orthogonal to the mean
"... It is shown that for many parametric families the condition for a parameter to be orthogonal to the mean takes on a particularly simple form. As a result, it is often possible to obtain analytically an explicit orthogonal parameter, thus providing insight into the many situations involving parametri ..."
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It is shown that for many parametric families the condition for a parameter to be orthogonal to the mean takes on a particularly simple form. As a result, it is often possible to obtain analytically an explicit orthogonal parameter, thus providing insight into the many situations involving
Results 1  10
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3,384