Estimation of subspace arrangements with applications in modeling and segmenting mixed data
Recently many scientific and engineering applications have involved the challenging task of
analyzing large amounts of unsorted high-dimensional data that have very complicated …
analyzing large amounts of unsorted high-dimensional data that have very complicated …
Provable self-representation based outlier detection in a union of subspaces
Many computer vision tasks involve processing large amounts of data contaminated by
outliers, which need to be detected and rejected. While outlier detection methods based on …
outliers, which need to be detected and rejected. While outlier detection methods based on …
Comparison and evaluation of dimensionality reduction techniques for the numerical simulations of unsteady cavitation
G Zhang, Z Wang, H Huang, H Li, T Sun - Physics of Fluids, 2023 - pubs.aip.org
In the field of fluid mechanics, dimensionality reduction (DR) is widely used for feature
extraction and information simplification of high-dimensional spatiotemporal data. It is well …
extraction and information simplification of high-dimensional spatiotemporal data. It is well …
Oblique projection for scalable rank-adaptive reduced-order modelling of nonlinear stochastic partial differential equations with time-dependent bases
Time-dependent basis reduced-order models (TDB ROMs) have successfully been used for
approximating the solution to nonlinear stochastic partial differential equations (PDEs). For …
approximating the solution to nonlinear stochastic partial differential equations (PDEs). For …
Low-rank representation with adaptive dictionary learning for subspace clustering
High-dimensional data are often treated as collections of data samples approximately drawn
from a union of multiple low-dimensional subspaces. Subspace clustering, where high …
from a union of multiple low-dimensional subspaces. Subspace clustering, where high …
Multiframe motion segmentation with missing data using PowerFactorization and GPCA
We consider the problem of segmenting multiple rigid-body motions from point
correspondences in multiple affine views. We cast this problem as a subspace clustering …
correspondences in multiple affine views. We cast this problem as a subspace clustering …
[HTML][HTML] Hybrid linear modeling via local best-fit flats
We present a simple and fast geometric method for modeling data by a union of affine
subspaces. The method begins by forming a collection of local best-fit affine subspaces, ie …
subspaces. The method begins by forming a collection of local best-fit affine subspaces, ie …
Motion segmentation via robust subspace separation in the presence of outlying, incomplete, or corrupted trajectories
We examine the problem of segmenting tracked feature point trajectories of multiple moving
objects in an image sequence. Using the affine camera model, this motion segmentation …
objects in an image sequence. Using the affine camera model, this motion segmentation …
Multi-scale dictionary learning using wavelets
In this paper, we present a multi-scale dictionary learning paradigm for sparse and
redundant signal representations. The appeal of such a dictionary is obvious-in many cases …
redundant signal representations. The appeal of such a dictionary is obvious-in many cases …