Results 1  10
of
4,138
Closedform solution of absolute orientation using unit quaternions
 J. Opt. Soc. Am. A
, 1987
"... Finding the relationship between two coordinate systems using pairs of measurements of the coordinates of a number of points in both systems is a classic photogrammetric task. It finds applications in stereophotogrammetry and in robotics. I present here a closedform solution to the leastsquares pr ..."
Abstract

Cited by 989 (4 self)
 Add to MetaCart
. These exact results are to be preferred to approximate methods based on measurements of a few selected points. The unit quaternion representing the best rotation is the eigenvector associated with the most positive eigenvalue of a symmetric 4 X 4 matrix. The elements of this matrix are combinations of sums
THE STRANGENESS RADIUS AND MAGNETIC MOMENT OF THE NUCLEON REVISITED #1
, 1995
"... We update Jaffe’s estimate of the strange isoscalar radius and magnetic moment of the nucleon. We make use of a recent dispersion–theoretical fit to the nucleon electromagnetic form factors and an improved description of symmetry breaking in the vector nonet. We find µs = −0.24 ± 0.03 n.m. and r2 s ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
s = 0.21 ± 0.03 fm2. The strange formfactor F s 2 (t) follows a dipole with a cut–off mass of 1.46 GeV, F s 2 (t) = µs(1 − t/2.14GeV 2) −2. These numbers should be considered as upper limits on the strange vector current matrix–elements in the nucleon. #1
From frequency to meaning : Vector space models of semantics
 Journal of Artificial Intelligence Research
, 2010
"... Computers understand very little of the meaning of human language. This profoundly limits our ability to give instructions to computers, the ability of computers to explain their actions to us, and the ability of computers to analyse and process text. Vector space models (VSMs) of semantics are begi ..."
Abstract

Cited by 347 (3 self)
 Add to MetaCart
are beginning to address these limits. This paper surveys the use of VSMs for semantic processing of text. We organize the literature on VSMs according to the structure of the matrix in a VSM. There are currently three broad classes of VSMs, based on term–document, word–context, and pair–pattern matrices
Online learning for matrix factorization and sparse coding
, 2010
"... Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statistics. This paper focuses on the largescale matrix factorization problem that consists of learning the basis set in order to ad ..."
Abstract

Cited by 330 (31 self)
 Add to MetaCart
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statistics. This paper focuses on the largescale matrix factorization problem that consists of learning the basis set in order
1 Strange matrix elements of the nucleon
, 2002
"... Results for the disconnected contributions to matrix elements of the vector current and scalar density have been obtained for the nucleon from the Wilson action at β = 6 using a stochastic estimator technique and 2000 quenched configurations. Various methods for analysis are employed and chiral extr ..."
Abstract
 Add to MetaCart
Results for the disconnected contributions to matrix elements of the vector current and scalar density have been obtained for the nucleon from the Wilson action at β = 6 using a stochastic estimator technique and 2000 quenched configurations. Various methods for analysis are employed and chiral
STRANGE VECTOR FORM FACTOR OF KAONS
, 2001
"... Starting from the ω − φ mixing, further assuming the coupling of the quarkcurrent of some flavour to be of universal strenth exclusively to the component of vectormeson wave function with the same flavour and finally taking numerical values of the coupling constant ratios (fωKK/f ¯ e ω), (fφKK/f ¯ ..."
Abstract
 Add to MetaCart
KK/f ¯ e φ) from the isoscalar part of a realistic sixresonance unitary and analytic model of the kaon electromagnetic structure, the strangequark vector current form factor behaviour of Kmesons in spacelike and timelike regions is predicted. PACS: 11.40.Ex, 12.40.Vv, 13.30.Gp, 13.40.Hq, 14.40.Aq
The chiral extrapolation of strange matrix elements
 in the nucleon, Phys. Rev. D66 (2002) 074509, [heplat/0207022
"... In current lattice simulations of nucleon properties, the up and down quark masses are significantly larger than their physical values, while the strange quark can be included in simulations with its physical mass. When the up and down quark masses are much smaller than the strangequark mass the ch ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
the chiral extrapolation of strangequark matrix elements in the nucleon from the lattice up and down quark masses to their physical values can be performed with twoflavor chiral perturbation theory, thereby avoiding the slow convergence problem of the threeflavor chiral expansion. We explore the chiral
KFA–IKP(TH)–1997–01 Strange vector currents and the OZI–rule
, 1997
"... We investigate the role of correlated πρ exchange in the extraction of matrix elements of the strange vector current in the proton. We show that a realistic isoscalar spectral function including this effect leads to sizeably reduced strange vector form factors based on the dispersion–theoretical ana ..."
Abstract
 Add to MetaCart
We investigate the role of correlated πρ exchange in the extraction of matrix elements of the strange vector current in the proton. We show that a realistic isoscalar spectral function including this effect leads to sizeably reduced strange vector form factors based on the dispersion
Efficient SVM training using lowrank kernel representations
 Journal of Machine Learning Research
, 2001
"... SVM training is a convex optimization problem which scales with the training set size rather than the feature space dimension. While this is usually considered to be a desired quality, in large scale problems it may cause training to be impractical. The common techniques to handle this difficulty ba ..."
Abstract

Cited by 240 (3 self)
 Add to MetaCart
basically build a solution by solving a sequence of small scale subproblems. Our current effort is concentrated on the rank of the kernel matrix as a source for further enhancement of the training procedure. We first show that for a low rank kernel matrix it is possible to design a better interior point
A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data
 Applications of Data Mining in Computer Security
, 2002
"... Abstract Most current intrusion detection systems employ signaturebased methods or data miningbased methods which rely on labeled training data. This training data is typically expensive to produce. We present a new geometric framework for unsupervised anomaly detection, which are algorithms that ..."
Abstract

Cited by 238 (9 self)
 Add to MetaCart
that are designed to process unlabeled data. In our framework, data elements are mapped to a feature space which is typically a vector space! d. Anomalies are detected by determining which points lies in sparse
Results 1  10
of
4,138