Examples of using High-dimensional in English and their translations into German
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Applicable in case of high-dimensional problems.
IBM SPSS Categoriesgives you all the tools for analysing complex categorical and high-dimensional data.
Although it may sound easy, in high-dimensional data it can be very difficult.
König researches methodological procedures, which enable the prediction of disease development and progression from high-dimensional data.
Numerical linear algebra for high-dimensional problems and efficient algorithms in data science.
People also translate
Of interest is the question of whether high-dimensional e. g.
The method is particularly suitable for high-dimensional, nonlinear tasks with extensive computational demands concerning the simulation.
One example are optimization problems in high-dimensional spaces.
Of special interest are the areas of high-dimensional statistics, computational methods for large-scale modeling, and causal inference.
Such models are used in particular to analyze and forecast high-dimensional time series.
High-dimensional statistical learning to advance economic and sustainability policies is at the centre of another two clusters of research topics.
They are structured on discrete lattices, often stochastic, high-dimensional and abstract, and they provide huge amounts of data.
It's focus lies on functional spectral methods on the basis of polynomial chaos expansions andthe treatment of high-dimensional discretizations.
Function values which are given by analytical expressions such as high-dimensional integrals are often not computable with a reasonble effort.
Particularly, as with the high-dimensional SNP data that are available today, a causative variant can be pinpointed to a specific base pair on the genome.
The new technique will be based on the state-of-the-art numerical methods for high-dimensional approximation and machine learning.
If modeling techniques are applied to high-dimensional multivariate problems, most methods fail to deliver a fair model because of the complexity of the data space.
To this end we have over several years studiedkey statistical issues that arise in complex, high-dimensional biomedical data.
Application fields are fluid dynamics, coupled multiphysics problems, high-dimensional problems such as data mining, time series predictions and quantification of uncertainties.
Model reduction aims at simplifying the governing equations byfinding low-dimensional models that approximate the full high-dimensional dynamics.
Your key advantages whenusing the ClearVu Global Optimizer applicable in case of high-dimensional problems broad applicability to simulation based objective functions and MDO.
For small, ubiquitous devices, the resource constraints are directly apparent, but they hold as well for largecomputing facilities in the case of extremely large, high-dimensional, dynamic data.
Initially building from the reference model, we set up a simplified, linear,but nevertheless high-dimensional surrogate model which represents the lehr in its various operating points.
High-Dimensional Data Analysis" to have a deeper understanding of emerging computational tools and"New Mathematical Tools for Contemporary Statistics" to develop new and more sophisticated statistical methods.
Developing numerical and statistical methods ormachine learning procedures to deal with a high-dimensional inverse problem in optics.
Quasi-Monte Carlo methods rely on- sometimes high-dimensional- point sets and sequences with particular distribution properties which are generated and analyzed with the help of number theoretical algorithms.
Within our research project MONREP(in cooperation with Prof. Konen, TH Cologne),we have developed a new optimization algorithm for high-dimensional, nonlinear, constrained applications.
During this time he madeimportant contributions to the theory of multiple tests for high-dimensional, spatially and time dependent, complex structured data, as well as to simultaneous statistical inference in general, which also continues to be the focus of his research.
ClearVu Global Optimizer for OPTIMUS: Nonlinear global optimization utilizing evolutionary strategies,specifically developed for high-dimensional applications on time-consuming numerical simulations e.g., FEM.
Numerical investigation of dictionary-based regularization for inverse problems and approximation problems on spheres and balls-with applications to seismic tomography and high-dimensional geophysical modelling", financed by the German Research Foundation DFG.