A Hyperspherical Adaptive Sparse-Grid Method for High-Dimensional Discontinuity Detection
نویسندگان
چکیده
منابع مشابه
A sparse grid based method for generative dimensionality reduction of high-dimensional data
Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a lowdimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative ...
متن کاملAdaptive Leja Sparse Grid Constructions for Stochastic Collocation and High-Dimensional Approximation
We propose an adaptive sparse grid stochastic collocation approach based upon Leja interpolation sequences for approximation of parameterized functions with high-dimensional parameters. Leja sequences are arbitrarily granular (any number of nodes may be added to a current sequence, producing a new sequence) and thus are a good choice for the univariate composite rule used to construct adaptive ...
متن کاملA New Dictionary Construction Method in Sparse Representation Techniques for Target Detection in Hyperspectral Imagery
Hyperspectral data in Remote Sensing which have been gathered with efficient spectral resolution (about 10 nanometer) contain a plethora of spectral bands (roughly 200 bands). Since precious information about the spectral features of target materials can be extracted from these data, they have been used exclusively in hyperspectral target detection. One of the problem associated with the detect...
متن کاملAn adaptive grid method for two-dimensional viscous flows
This paper extends the gas-kinetic BGK-NS scheme to an adaptive grid for the viscous flow simulations. The grid movement and adaptation is controlled by a monitor function which may depend on velocity gradient or other flow variables, such as density or pressure. For the viscous flow computation, the use of adaptive mesh much improves the efficiency and accuracy of the method in comparison with...
متن کاملAdaptive Sparse Grid Classification Using Grid Environments
Common techniques tackling the task of classification in data mining employ ansatz functions associated to training data points to fit the data as well as possible. Instead, the feature space can be discretized and ansatz functions centered on grid points can be used. This allows for classification algorithms scaling only linearly in the number of training data points, enabling to learn from da...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SIAM Journal on Numerical Analysis
سال: 2015
ISSN: 0036-1429,1095-7170
DOI: 10.1137/140971531