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Comparative Study of Various Approximations to the Covariance Matrix in Template Attacks
DES TDES Template Attack
2016/12/24
Template attacks have been shown to be among the strongest attacks when it comes to side–channel attacks. An essential ingredient there is to calculate the inverse of a covariance matrix. In this pape...
Time and Fermions:General Covariance vs.Ockham's Razor for Spinors
spinor fermion general covariance geometric object nonlinear group realization conventionality of simultaneity Schwarzschild solution
2016/6/15
It is a commonplace in the foundations of physics, attributed to Kretschmann, that any local physical theory can be represented using arbitrary coordinates, simply by using tensor calculus. On the oth...
Operational understanding of the covariance of classical electrodynamics
Operationalism Covariance of Classical Electrodynamics Empirical Verification Transformation Rule Maxwell–Lorentz Equations
2016/6/13
It is common in the literature on classical electrodynamics and relativity theory that the transformation rules for the basic electrodynamic quantities are derived from the pre-assumption that the equ...
General Covariance and Background Independence in Quantum Gravity
general covariance background independence quantum gravity string theory loop quantum gravity spin foam models
2016/5/27
The history of general relativity suggests that in absence of experi-mental data, constructing a theory on philosophical first principles can lead to a very useful theory as well as to ground-breaking...
Testing the Diagonality of a Large Covariance Matrix in a Regression Setting
Bias-Corrected Test Covariance Diagonality Test High Di- mensional Data
2016/1/26
In multivariate analysis, the covariance matrix associated with a set of vari-ables of interest (namely response variables) commonly contains valuable infor-mation about the dataset. When the dimensio...
Band Width Selection for High Dimensional Covariance Matrix Estimation
Bandable covariance Banding estimator Large p, small n Ratio- consistency Tapering estimator Thresholding estimator
2016/1/25
The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (2010), are important high dimensional covariance esti-mators. Both estimators require choosing a ban...
Test for Bandedness of High-Dimensional Covariance Matrices and Bandwidth Estimation
Banded covariance matrix Bandwidth estimation High data dimension Large p small n Nonparametric
2016/1/25
Motivated by the latest effort to employ banded matrices to esti-mate a high-dimensional covariance Σ, we propose a test for Σ being banded with possible diverging bandwidth. The test is adaptive to t...
Testing the Diagonality of a Large Covariance Matrix in a Regression Setting
Bias-Corrected Test Covariance Diagonality Test High Di- mensional Data Multivariate Analysis
2016/1/20
In multivariate analysis, the covariance matrix associated with a set of vari-ables of interest (namely response variables) commonly contains valuable infor-mation about the dataset. When the dimensio...
Band Width Selection for High Dimensional Covariance Matrix Estimation
Bandable covariance Banding estimator Large p small n
2016/1/20
The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (2010), are important high dimensional covariance esti-mators. Both estimators require choosing a ban...
Test for Bandedness of High-Dimensional Covariance Matrices and Bandwidth Estimation
Banded covariance matrix Bandwidth estimation High data dimension Large p small n Nonparametric
2016/1/20
Motivated by the latest effort to employ banded matrices to esti-mate a high-dimensional covariance Σ, we propose a test for Σ being banded with possible diverging bandwidth. The test is adaptive to t...
Range Image Sequence Analysis by 2.5-D Least-Squares-Tracking with Variance Component Estimation and Robust Variance Covariance Matrix Estimation
Range Imaging Least Squares Tracking Variance Component Estimation
2015/12/17
In this article, a range image sequence tracking approach is proposed, which combines 3-D camera intensity and range observations
in an integrated geometric transformation model. Based on 2-D least s...
ELUCIDATING PHYSIOLOGY OF PLANT MEDIATED EXCHANGE PROCESSES USING AIRBORNE HYPERSPECTRAL REFLECTANCE MEASUREMENTS IN SYNOPSIS WITH EDDY COVARIANCE DATA
Remote Sensing CERES vegetation
2015/9/8
The Carbo Europe Regional Experiment Strategy (CERES), conducted between May and June 2005, aims to determine a spatially
resolved regional balance of carbon dioxide fluxes using different methodolog...
Sparse inverse covariance estimation with the lasso
Sparse inverse covariance estimation the lasso
2015/8/21
We consider the problem of estimating sparse graphs by a lasso penalty applied to the inverse covariance matrix. Using a coordinate descent procedure for the lasso, we develop a simple algorithm— the ...
Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso
sparse inverse covariance selection sparsity graphical lasso Gaussian graphical models graph connected components concentration graph large scale covariance estimation
2015/8/21
We consider the sparse inverse covariance regularization problem or graphical lasso with regularization parameter λ. Suppose the sample covariance graph formed by thresholding the entries of the sampl...
A FRAMEWORK FOR POSITION UNCERTAINTY OF UNORGANISED THREE-DIMENSIONAL POINT CLOUDS FROM NEAR-MONOSTATIC LASER SCANNERS USING COVARIANCE ANALYSIS
Position uncertainty Three-dimensional Point Cloud Laser Scanning
2015/8/13
Position uncertainty is one of the most important quantities of an unorganised three-dimensional point clouds since it
provides the confidence level of any parametric estimation such as surface...