Results 1  10
of
3,208
On the Selfsimilar Nature of Ethernet Traffic (Extended Version)
, 1994
"... We demonstrate that Ethernet LAN traffic is statistically selfsimilar, that none of the commonly used traffic models is able to capture this fractallike behavior, that such behavior has serious implications for the design, control, and analysis of highspeed, cellbased networks, and that aggrega ..."
Abstract

Cited by 2213 (46 self)
 Add to MetaCart
, and that aggregating streams of such traffic typically intensifies the selfsimilarity (“burstiness”) instead of smoothing it. Our conclusions are supported by a rigorous statistical analysis of hundreds of millions of high quality Ethernet traffic measurements collected between 1989 and 1992, coupled with a
Smoothed Versions of Statistical Functionals from a Finite Population
"... We consider smoothed version of the empirical distribution functions from the finite population and the asymptotic behavior of the statistical functionals defined on the class of smoothed empirical distribution functions. Main parts of our results correspond to those of Fernholz (1991, 1993) in I.I. ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
We consider smoothed version of the empirical distribution functions from the finite population and the asymptotic behavior of the statistical functionals defined on the class of smoothed empirical distribution functions. Main parts of our results correspond to those of Fernholz (1991, 1993) in I
Implementing approximate Bayesian inference for latent Gaussian models using integrated nested Laplace approximations: A manual for the inlaprogram
, 2008
"... Structured additive regression models are perhaps the most commonly used class of models in statistical applications. It includes, among others, (generalised) linear models, (generalised) additive models, smoothingspline models, statespace models, semiparametric regression, spatial and spatiotemp ..."
Abstract

Cited by 294 (20 self)
 Add to MetaCart
Structured additive regression models are perhaps the most commonly used class of models in statistical applications. It includes, among others, (generalised) linear models, (generalised) additive models, smoothingspline models, statespace models, semiparametric regression, spatial and spatio
Regularized estimation of large covariance matrices
 Ann. Statist
, 2008
"... This paper considers estimating a covariance matrix of p variables from n observations by either banding or tapering the sample covariance matrix, or estimating a banded version of the inverse of the covariance. We show that these estimates are consistent in the operator norm as long as (log p)/n → ..."
Abstract

Cited by 185 (14 self)
 Add to MetaCart
conditioned, then the banded approximations produce consistent estimates of the eigenvalues and associated eigenvectors of the covariance matrix. The results can be extended to smooth versions of banding and to nonGaussian distributions with sufficiently short tails. A resampling approach is proposed for choosing the banding
The Inverse Mean Curvature Flow and the Riemannian Penrose Inequality
 J. DIFFERENTIAL GEOM
, 1998
"... In this paper we develop the theory of weak solutions for the inverse mean curvature flow of hypersurfaces in a Riemannian manifold, and apply it to prove the Riemannian version of the Penrose inequality for the total mass of an asymptotically flat 3manifold of nonnegative scalar curvature, announc ..."
Abstract

Cited by 201 (0 self)
 Add to MetaCart
In this paper we develop the theory of weak solutions for the inverse mean curvature flow of hypersurfaces in a Riemannian manifold, and apply it to prove the Riemannian version of the Penrose inequality for the total mass of an asymptotically flat 3manifold of nonnegative scalar curvature
Anisotropic Polygonal Remeshing
"... In this paper, we propose a novel polygonal remeshing technique that exploits a key aspect of surfaces: the intrinsic anisotropy of natural or manmade geometry. In particular, we use curvature directions to drive the remeshing process, mimicking the lines that artists themselves would use when cre ..."
Abstract

Cited by 203 (16 self)
 Add to MetaCart
creating 3D models from scratch. After extracting and smoothing the curvature tensor field of an input genus0 surface patch, lines of minimum and maximum curvatures are used to determine appropriate edges for the remeshed version in anisotropic regions, while spherical regions are simply pointsampled
Optimal Taxation without StateContingent Debt
, 1996
"... To recover a version of Barro's (1979) `random walk' tax smoothing outcome, we modify Lucas and Stokey's (1983) economy to permit only riskfree debt. This imparts near unit root like behavior to government debt, independently of the government expenditure process, a realistic outcome ..."
Abstract

Cited by 201 (20 self)
 Add to MetaCart
To recover a version of Barro's (1979) `random walk' tax smoothing outcome, we modify Lucas and Stokey's (1983) economy to permit only riskfree debt. This imparts near unit root like behavior to government debt, independently of the government expenditure process, a realistic
Smooth Operators
"... We develop a generic approach to form smooth versions of basic mathematical operations like multiplication, composition, change of measure, and conditional expectation, among others. Operations which result in functions outside the reproducing kernel Hilbert space (such as the product of two RKHS fu ..."
Abstract

Cited by 8 (4 self)
 Add to MetaCart
We develop a generic approach to form smooth versions of basic mathematical operations like multiplication, composition, change of measure, and conditional expectation, among others. Operations which result in functions outside the reproducing kernel Hilbert space (such as the product of two RKHS
A fast approximation of the bilateral filter using a signal processing approach
 In Proceedings of the European Conference on Computer Vision
, 2006
"... The bilateral filter is a nonlinear filter that smoothes a signal while preserving strong edges. It has demonstrated great effectiveness for a variety of problems in computer vision and computer graphics, and fast versions have been proposed. Unfortunately, little is known about the accuracy of such ..."
Abstract

Cited by 179 (7 self)
 Add to MetaCart
The bilateral filter is a nonlinear filter that smoothes a signal while preserving strong edges. It has demonstrated great effectiveness for a variety of problems in computer vision and computer graphics, and fast versions have been proposed. Unfortunately, little is known about the accuracy
Evolutionary Spectral Clustering by Incorporating Temporal Smoothness
, 2007
"... Evolutionary clustering is an emerging research area essential to important applications such as clustering dynamic Web and blog contents and clustering data streams. In evolutionary clustering, a good clustering result should fit the current data well, while simultaneously not deviate too dramatica ..."
Abstract

Cited by 92 (8 self)
 Add to MetaCart
dramatically from the recent history. To fulfill this dual purpose, a measure of temporal smoothness is integrated in the overall measure of clustering quality. In this paper, we propose two frameworks that incorporate temporal smoothness in evolutionary spectral clustering. For both frameworks, we start
Results 1  10
of
3,208